Search results for: thermal network
3102 Economic Analysis of Domestic Combined Heat and Power System in the UK
Authors: Thamo Sutharssan, Diogo Montalvao, Wen-Chung Wang, Yong Chen, Claudia Pisac
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A combined heat and power (CHP) system is an efficient and clean way to generate power (electricity). Heat produced by the CHP system can be used for water and space heating. The CHP system which uses hydrogen as fuel produces zero carbon emission. Its’ efficiency can reach more than 80% whereas that of a traditional power station can only reach up to 50% because much of the thermal energy is wasted. The other advantages of CHP systems include that they can decentralize energy generation, improve energy security and sustainability, and significantly reduce the energy cost to the users. This paper presents the economic benefits of using a CHP system in the domestic environment. For this analysis, natural gas is considered as potential fuel as the hydrogen fuel cell based CHP systems are rarely used. UK government incentives for CHP systems are also considered as the added benefit. Results show that CHP requires a significant initial investment in return it can reduce the annual energy bill significantly. Results show that an investment may be paid back in 7 years. After the back period, CHP can run for about 3 years as most of the CHP manufacturers provide 10-year warranty.Keywords: combined heat and power, clean energy, hydrogen fuel cell, economic analysis of CHP, zero emission
Procedia PDF Downloads 3853101 Image Compression Using Block Power Method for SVD Decomposition
Authors: El Asnaoui Khalid, Chawki Youness, Aksasse Brahim, Ouanan Mohammed
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In these recent decades, the important and fast growth in the development and demand of multimedia products is contributing to an insufficient in the bandwidth of device and network storage memory. Consequently, the theory of data compression becomes more significant for reducing the data redundancy in order to save more transfer and storage of data. In this context, this paper addresses the problem of the lossless and the near-lossless compression of images. This proposed method is based on Block SVD Power Method that overcomes the disadvantages of Matlab's SVD function. The experimental results show that the proposed algorithm has a better compression performance compared with the existing compression algorithms that use the Matlab's SVD function. In addition, the proposed approach is simple and can provide different degrees of error resilience, which gives, in a short execution time, a better image compression.Keywords: image compression, SVD, block SVD power method, lossless compression, near lossless
Procedia PDF Downloads 3873100 Influence of Silicon Carbide Particle Size and Thermo-Mechanical Processing on Dimensional Stability of Al 2124SiC Nanocomposite
Authors: Mohamed M. Emara, Heba Ashraf
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This study is to investigation the effect of silicon carbide (SiC) particle size and thermo-mechanical processing on dimensional stability of aluminum alloy 2124. Three combinations of SiC weight fractions are investigated, 2.5, 5, and 10 wt. % with different SiC particle sizes (25 μm, 5 μm, and 100nm) were produced using mechanical ball mill. The standard testing samples were fabricated using powder metallurgy technique. Both samples, prior and after extrusion, were heated from room temperature up to 400ºC in a dilatometer at different heating rates, that is, 10, 20, and 40ºC/min. The analysis showed that for all materials, there was an increase in length change as temperature increased and the temperature sensitivity of aluminum alloy decreased in the presence of both micro and nano-sized silicon carbide. For all conditions, nanocomposites showed better dimensional stability compared to conventional Al 2124/SiC composites. The after extrusion samples showed better thermal stability and less temperature sensitivity for the aluminum alloy for both micro and nano-sized silicon carbide.Keywords: aluminum 2124 metal matrix composite, SiC nano-sized reinforcements, powder metallurgy, extrusion mechanical ball mill, dimensional stability
Procedia PDF Downloads 5263099 Emerging Virtual Linguistic Landscape Created by Members of Language Community in TikTok
Authors: Kai Zhu, Shanhua He, Yujiao Chang
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This paper explores the virtual linguistic landscape of an emerging virtual language community in TikTok, a language community realizing immediate and non-immediate communication without a precise Spatio-temporal domain or a specific socio-cultural boundary or interpersonal network. This kind of language community generates a large number and various forms of virtual linguistic landscape, with which we conducted a virtual ethnographic survey together with telephone interviews to collect data from coping. We have been following two language communities in TikTok for several months so that we can illustrate the composition of the two language communities and some typical virtual language landscapes in both language communities first. Then we try to explore the reasons why and how they are formed through the organization, transcription, and analysis of the interviews. Our analysis reveals the richness and diversity of the virtual linguistic landscape, and finally, we summarize some of the characteristics of this language community.Keywords: virtual linguistic landscape, virtual language community, virtual ethnographic survey, TikTok
Procedia PDF Downloads 1043098 A Model-Based Approach for Energy Performance Assessment of a Spherical Stationary Reflector/Tracking Absorber Solar Concentrator
Authors: Rosa Christodoulaki, Irene Koronaki, Panagiotis Tsekouras
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The aim of this study is to analyze the energy performance of a spherical Stationary Reflector / Tracking Absorber (SRTA) solar concentrator. This type of collector consists of a segment of a spherical mirror placed in a stationary position facing the sun and a cylindrical absorber that tracks the sun by a simple pivoting motion about the center of curvature of the reflector. The energy analysis is performed through the development of a dynamic simulation model in TRNSYS software that calculates the annual heat production and the efficiency of the SRTA solar concentrator. The effect of solar concentrator design features and characteristics, such the reflector material, the reflector diameter, the receiver type, the solar radiation level and the concentration ratio, are discussed in details. Moreover, the energy performance curve of the SRTA solar concentrator, for various temperature differences between the mean fluid temperature and the ambient temperature and radiation intensities is drawn. The results are shown in diagrams, visualizing the effect of solar, optical and thermal parameters to the overall performance of the SRTA solar concentrator throughout the year. The analysis indicates that the SRTA solar concentrator can operate efficiently under a wide range of operating conditions.Keywords: concentrating solar collector, energy analysis , stationary reflector, tracking absorber
Procedia PDF Downloads 2013097 The Effect of Feature Selection on Pattern Classification
Authors: Chih-Fong Tsai, Ya-Han Hu
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The aim of feature selection (or dimensionality reduction) is to filter out unrepresentative features (or variables) making the classifier perform better than the one without feature selection. Since there are many well-known feature selection algorithms, and different classifiers based on different selection results may perform differently, very few studies consider examining the effect of performing different feature selection algorithms on the classification performances by different classifiers over different types of datasets. In this paper, two widely used algorithms, which are the genetic algorithm (GA) and information gain (IG), are used to perform feature selection. On the other hand, three well-known classifiers are constructed, which are the CART decision tree (DT), multi-layer perceptron (MLP) neural network, and support vector machine (SVM). Based on 14 different types of datasets, the experimental results show that in most cases IG is a better feature selection algorithm than GA. In addition, the combinations of IG with DT and IG with SVM perform best and second best for small and large scale datasets.Keywords: data mining, feature selection, pattern classification, dimensionality reduction
Procedia PDF Downloads 6693096 Heart-Rate Resistance Electrocardiogram Identification Based on Slope-Oriented Neural Networks
Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang
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For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network
Procedia PDF Downloads 4353095 Properties and Antimicrobial Activity of Fish Protein Isolate/Fish Skin Gelatin Film Containing Basil Leaf Essential Oil and Zinc Oxide Nanoparticles
Authors: Yasir Ali Arfat
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Composite films based on fish protein isolate (FPI) and fish skin gelatin (FSG) blend incorporated with 50 and 100% (w/w, protein) basil leaf essential oil (BEO) in the absence and presence of 3% (w/w, protein) ZnO nanoparticles (ZnONP) were prepared and characterised. Tensile strength (TS) decreased, whilst elongation at break (EAB) increased as BEO level increased (p < 0.05). However, ZnONP addition resulted in higher TS but lower EAB (p < 0.05). The lowest water vapour permeability (WVP) was observed for the film incorporated with 100% BEO and 3% ZnONP (p < 0.05). BEO and ZnONP incorporation decreased transparency of FPI/FSG films (p < 0.05). FTIR spectra indicated that films added with BEO exhibited higher hydrophobicity. Both BEO and ZnONP had a marked impact on thermal stability of the films. Microstructural study revealed that presence of ZnONP prevented bilayer formation of film containing 100% BEO. FPI/FSG films incorporated with 100% BEO, especially in combination with ZnONP, exhibited strong antibacterial activity against food pathogenic and spoilage bacteria and thus could be used as an active food packaging material to ensure safety and to extend the shelf-life of packaged foods.Keywords: bionanocomposite, fish protein isolate, fish skin gelatin, basil essential oil, ZnO nanoparticles, antimicrobial packaging
Procedia PDF Downloads 4713094 Energy Efficiency Analysis of Discharge Modes of an Adiabatic Compressed Air Energy Storage System
Authors: Shane D. Inder, Mehrdad Khamooshi
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Efficient energy storage is a crucial factor in facilitating the uptake of renewable energy resources. Among the many options available for energy storage systems required to balance imbalanced supply and demand cycles, compressed air energy storage (CAES) is a proven technology in grid-scale applications. This paper reviews the current state of micro scale CAES technology and describes a micro-scale advanced adiabatic CAES (A-CAES) system, where heat generated during compression is stored for use in the discharge phase. It will also describe a thermodynamic model, developed in EES (Engineering Equation Solver) to evaluate the performance and critical parameters of the discharge phase of the proposed system. Three configurations are explained including: single turbine without preheater, two turbines with preheaters, and three turbines with preheaters. It is shown that the micro-scale A-CAES is highly dependent upon key parameters including; regulator pressure, air pressure and volume, thermal energy storage temperature and flow rate and the number of turbines. It was found that a micro-scale AA-CAES, when optimized with an appropriate configuration, could deliver energy input to output efficiency of up to 70%.Keywords: CAES, adiabatic compressed air energy storage, expansion phase, micro generation, thermodynamic
Procedia PDF Downloads 3113093 Development of a BriMAIN System for Health Monitoring of Railway Bridges
Authors: Prakher Mishra, Dikshant Bodana, Saloni Desai, Sudhanshu Dixit, Sopan Agarwal, Shriraj Patel
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Railways are sometimes lifeline of nations as they consist of huge network of rail lines and bridges. Reportedly many of the bridges are aging, weak, distressed and accident prone. It becomes a really challenging task for Engineers and workers to keep up a regular maintenance schedule for proper functioning which itself is quite a hard hitting job. In this paper we have come up with an innvovative wireless system of maintenance called BriMAIN. In this system we have installed two types of sensors, first one is called a force sensor which will continously analyse the readings of pressure at joints of the bridges and secondly an MPU-6050 triaxial gyroscope+accelerometer which will analyse the deflection of the deck of the bridge. Apart from this a separate database is also being made at the server room so that the data can be visualized by the engineers and a warning can be issued in case reading of the sensors goes above threshold.Keywords: Accelerometer, B-MAIN, Gyroscope, MPU-6050
Procedia PDF Downloads 3833092 Efficient Neural and Fuzzy Models for the Identification of Dynamical Systems
Authors: Aouiche Abdelaziz, Soudani Mouhamed Salah, Aouiche El Moundhe
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The present paper addresses the utilization of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FISs) for the identification and control of dynamical systems with some degree of uncertainty. Because ANNs and FISs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controllers. In this work, we show how ANNs and FISs can be put in order to form nets that can learn from external data. In sequence, it is presented structures of inputs that can be used along with ANNs and FISs to model non-linear systems. Four systems were used to test the identification and control of the structures proposed. The results show the ANNs and FISs (Back Propagation Algorithm) used were efficient in modeling and controlling the non-linear plants.Keywords: non-linear systems, fuzzy set Models, neural network, control law
Procedia PDF Downloads 2123091 Evaluation of Parameters of Subject Models and Their Mutual Effects
Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov
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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.Keywords: dispersed systems, models, hydraulic network, algorithms
Procedia PDF Downloads 2843090 Financial Assets Return, Economic Factors and Investor's Behavioral Indicators Relationships Modeling: A Bayesian Networks Approach
Authors: Nada Souissi, Mourad Mroua
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The main purpose of this study is to examine the interaction between financial asset volatility, economic factors and investor's behavioral indicators related to both the company's and the markets stocks for the period from January 2000 to January2020. Using multiple linear regression and Bayesian Networks modeling, results show a positive and negative relationship between investor's psychology index, economic factors and predicted stock market return. We reveal that the application of the Bayesian Discrete Network contributes to identify the different cause and effect relationships between all economic, financial variables and psychology index.Keywords: Financial asset return predictability, Economic factors, Investor's psychology index, Bayesian approach, Probabilistic networks, Parametric learning
Procedia PDF Downloads 1503089 Directional Solidification of Al–Cu–Mg Eutectic Alloy
Authors: Yusuf Kaygısız, Necmetti̇n Maraşlı
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Aluminum alloys are produced and used at various areas of industry and especially in the aerospace industry. The advantages of these alloys over traditional iron-based alloys are lightweight, corrosion resistance, and very good thermal and electrical conductivity. The aim of this work is to experimentally investigate the effect of growth rates on the eutectic spacings (λ), microhardness, tensile strength and electrical resistivity in Al–30wt.%Cu–6wt.%Mg eutectic alloy. Al–Cu–Mg eutectic alloy was directionally solidified at a constant temperature gradient (G=8.55 K/mm) with different growth rates, 9.43 to 173.3 µm/s by using a Bridgman-type furnace. The dependency of microstructure, microhardness, tensile strength and electrical resistivity for directionally solidified the Al-Cu-Mg eutectic alloy were investigated. Eutectic microstructure is consisting of regular Al2CuMg lamellar and Al2Cu rod phases with in the α (Al) solid solution matrix. The lamellar eutectic spacings were measured from transverse sections of the samples. It was found that the value of microstructures decrease with the increase the value the growth rates. The microhardness, tensile strength and electrical resistivity of the alloy also were measured from sample and relationships between them were experimentally analyzed by using regression analysis. According to present results, values tensile strength and electrical resistivity increase with increasing growth rates.Keywords: directional solidification, aluminum alloys, microstructure, electrical properties, hardness test
Procedia PDF Downloads 2943088 TiO2/Clay Minerals (Palygorskite/Halloysite) Nanocomposite Coatings for Water Disinfection
Authors: Dionisios Panagiotaras, Dimitrios Papoulis, Elias Stathatos
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Microfibrous palygorskite and tubular halloysite clay mineral combined with nanocrystalline TiO2 are incorporating in the preparation of nanocomposite films on glass substrates via sol-gel route at 450 °C. The synthesis is employing nonionic surfactant molecule as pore directing agent along with acetic acid-based sol-gel route without addition of water molecules. Drying and thermal treatment of composite films ensure elimination of organic material lead to the formation of TiO2 nanoparticles homogeneously distributed on the palygorskite or halloysite surfaces. Nanocomposite films without cracks of active anatase crystal phase on palygorskite and halloysite surfaces are characterized by microscopy techniques, UV-Vis spectroscopy, and porosimetry methods in order to examine their structural properties. The composite palygorskite-TiO2 and halloysite-TiO2 films with variable quantities of palygorskite and halloysite were tested as photocatalysts in the photo-oxidation of Basic Blue 41 azo dye in water. These nanocomposite films proved to be most promising photocatalysts and highly effective to dye’s decoloration in spite of small amount of palygorskite -TiO2 or halloysite- TiO2 catalyst immobilized onto glass substrates mainly due to the high surface area and uniform distribution of TiO2 on clay minerals avoiding aggregation.Keywords: halloysite, palygorskite, photocatalysis, titanium dioxide
Procedia PDF Downloads 3153087 Dynamic EEG Desynchronization in Response to Vicarious Pain
Authors: Justin Durham, Chanda Rooney, Robert Mather, Mickie Vanhoy
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The psychological construct of empathy is to understand a person’s cognitive perspective and experience the other person’s emotional state. Deciphering emotional states is conducive for interpreting vicarious pain. Observing others' physical pain activates neural networks related to the actual experience of pain itself. The study addresses empathy as a nonlinear dynamic process of simulation for individuals to understand the mental states of others and experience vicarious pain, exhibiting self-organized criticality. Such criticality follows from a combination of neural networks with an excitatory feedback loop generating bistability to resonate permutated empathy. Cortical networks exhibit diverse patterns of activity, including oscillations, synchrony and waves, however, the temporal dynamics of neurophysiological activities underlying empathic processes remain poorly understood. Mu rhythms are EEG oscillations with dominant frequencies of 8-13 Hz becoming synchronized when the body is relaxed with eyes open and when the sensorimotor system is in idle, thus, mu rhythm synchrony is expected to be highest in baseline conditions. When the sensorimotor system is activated either by performing or simulating action, mu rhythms become suppressed or desynchronize, thus, should be suppressed while observing video clips of painful injuries if previous research on mirror system activation holds. Twelve undergraduates contributed EEG data and survey responses to empathy and psychopathy scales in addition to watching consecutive video clips of sports injuries. Participants watched a blank, black image on a computer monitor before and after observing a video of consecutive sports injuries incidents. Each video condition lasted five-minutes long. A BIOPAC MP150 recorded EEG signals from sensorimotor and thalamocortical regions related to a complex neural network called the ‘pain matrix’. Physical and social pain are activated in this network to resonate vicarious pain responses to processing empathy. Five EEG single electrode locations were applied to regions measuring sensorimotor electrical activity in microvolts (μV) to monitor mu rhythms. EEG signals were sampled at a rate of 200 Hz. Mu rhythm desynchronization was measured via 8-13 Hz at electrode sites (F3 & F4). Data for each participant’s mu rhythms were analyzed via Fast Fourier Transformation (FFT) and multifractal time series analysis.Keywords: desynchronization, dynamical systems theory, electroencephalography (EEG), empathy, multifractal time series analysis, mu waveform, neurophysiology, pain simulation, social cognition
Procedia PDF Downloads 2833086 Budgetary Performance Model for Managing Pavement Maintenance
Authors: Vivek Hokam, Vishrut Landge
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An ideal maintenance program for an industrial road network is one that would maintain all sections at a sufficiently high level of functional and structural conditions. However, due to various constraints such as budget, manpower and equipment, it is not possible to carry out maintenance on all the needy industrial road sections within a given planning period. A rational and systematic priority scheme needs to be employed to select and schedule industrial road sections for maintenance. Priority analysis is a multi-criteria process that determines the best ranking list of sections for maintenance based on several factors. In priority setting, difficult decisions are required to be made for selection of sections for maintenance. It is more important to repair a section with poor functional conditions which includes uncomfortable ride etc. or poor structural conditions i.e. sections those are in danger of becoming structurally unsound. It would seem therefore that any rational priority setting approach must consider the relative importance of functional and structural condition of the section. The maintenance priority index and pavement performance models tend to focus mainly on the pavement condition, traffic criteria etc. There is a need to develop the model which is suitably used with respect to limited budget provisions for maintenance of pavement. Linear programming is one of the most popular and widely used quantitative techniques. A linear programming model provides an efficient method for determining an optimal decision chosen from a large number of possible decisions. The optimum decision is one that meets a specified objective of management, subject to various constraints and restrictions. The objective is mainly minimization of maintenance cost of roads in industrial area. In order to determine the objective function for analysis of distress model it is necessary to fix the realistic data into a formulation. Each type of repair is to be quantified in a number of stretches by considering 1000 m as one stretch. A stretch considered under study is having 3750 m length. The quantity has to be put into an objective function for maximizing the number of repairs in a stretch related to quantity. The distress observed in this stretch are potholes, surface cracks, rutting and ravelling. The distress data is measured manually by observing each distress level on a stretch of 1000 m. The maintenance and rehabilitation measured that are followed currently are based on subjective judgments. Hence, there is a need to adopt a scientific approach in order to effectively use the limited resources. It is also necessary to determine the pavement performance and deterioration prediction relationship with more accurate and economic benefits of road networks with respect to vehicle operating cost. The infrastructure of road network should have best results expected from available funds. In this paper objective function for distress model is determined by linear programming and deterioration model considering overloading is discussed.Keywords: budget, maintenance, deterioration, priority
Procedia PDF Downloads 2073085 A Formal Microlectic Framework for Biological Circularchy
Authors: Ellis D. Cooper
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“Circularchy” is supposed to be an adjustable formal framework with enough expressive power to articulate biological theory about Earthly Life in the sense of multi-scale biological autonomy constrained by non-equilibrium thermodynamics. “Formal framework” means specifically a multi-sorted first-order-theorywithequality (for each sort). Philosophically, such a theory is one kind of “microlect,” which means a “way of speaking” (or, more generally, a “way of behaving”) for overtly expressing a “mental model” of some “referent.” Other kinds of microlect include “natural microlect,” “diagrammatic microlect,” and “behavioral microlect,” with examples such as “political theory,” “Euclidean geometry,” and “dance choreography,” respectively. These are all describable in terms of a vocabulary conforming to grammar. As aspects of human culture, they are possibly reminiscent of Ernst Cassirer’s idea of “symbolic form;” as vocabularies, they are akin to Richard Rorty’s idea of “final vocabulary” for expressing a mental model of one’s life. A formal microlect is presented by stipulating sorts, variables, calculations, predicates, and postulates. Calculations (a.k.a., “terms”) may be composed to form more complicated calculations; predicates (a.k.a., “relations”) may be logically combined to form more complicated predicates; and statements (a.k.a., “sentences”) are grammatically correct expressions which are true or false. Conclusions are statements derived using logical rules of deduction from postulates, other assumed statements, or previously derived conclusions. A circularchy is a formal microlect constituted by two or more sub-microlects, each with its distinct stipulations of sorts, variables, calculations, predicates, and postulates. Within a sub-microlect some postulates or conclusions are equations which are statements that declare equality of specified calculations. An equational bond between an equation in one sub-microlect and an equation in either the same sub-microlect or in another sub-microlect is a predicate that declares equality of symbols occurring in a side of one equation with symbols occurring in a side of the other equation. Briefly, a circularchy is a network of equational bonds between sub-microlects. A circularchy is solvable if there exist solutions for all equations that satisfy all equational bonds. If a circularchy is not solvable, then a challenge would be to discover the obstruction to solvability and then conjecture what adjustments might remove the obstruction. Adjustment means changes in stipulated ingredients (sorts, etc.) of sub-microlects, or changes in equational bonds between sub-microlects, or introduction of new sub-microlects and new equational bonds. A circularchy is modular insofar as each sub-microlect is a node in a network of equation bonds. Solvability of a circularchy may be conjectured. Efforts to prove solvability may be thwarted by a counter-example or may lead to the construction of a solution. An automated theorem-proof assistant would likely be necessary for investigating a substantial circularchy, such as one purported to represent Earthly Life. Such investigations (chains of statements) would be concurrent with and no substitute for simulations (chains of numbers).Keywords: autonomy, first-order theory, mathematics, thermodynamics
Procedia PDF Downloads 2203084 Multimedia Firearms Training System
Authors: Aleksander Nawrat, Karol Jędrasiak, Artur Ryt, Dawid Sobel
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The goal of the article is to present a novel Multimedia Firearms Training System. The system was developed in order to compensate for major problems of existing shooting training systems. The designed and implemented solution can be characterized by five major advantages: algorithm for automatic geometric calibration, algorithm of photometric recalibration, firearms hit point detection using thermal imaging camera, IR laser spot tracking algorithm for after action review analysis, and implementation of ballistics equations. The combination of the abovementioned advantages in a single multimedia firearms training system creates a comprehensive solution for detecting and tracking of the target point usable for shooting training systems and improving intervention tactics of uniformed services. The introduced algorithms of geometric and photometric recalibration allow the use of economically viable commercially available projectors for systems that require long and intensive use without most of the negative impacts on color mapping of existing multi-projector multimedia shooting range systems. The article presents the results of the developed algorithms and their application in real training systems.Keywords: firearms shot detection, geometric recalibration, photometric recalibration, IR tracking algorithm, thermography, ballistics
Procedia PDF Downloads 2233083 Cerium Salt Effect in 70s Bioactive Glass
Authors: Alessandra N. Santos, Max P. Ferreira, Alexandra R. P. Silva, Agda A. R. de Oliveira, Marivalda M. Pereira
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The literature describes experiments, in which ceria nanoparticles in the bioactive glass significantly improve differentiation of stem cells into osteoblasts and increase production of collagen. It is not known whether this effect observed due to the presence of nanoceria can be also observed in the presence of cerium in the bioactive glass network. The effect of cerium into bioactive glasses using the sol–gel route is the focus of this work, with the goal to develop a material for tissue engineering with the potential to enhance osteogenesis. A bioactive glass composition based on 70% SiO2–30% CaO is produced with the addition of cerium. The analyses XRD, FTIR, SEM/EDS, BET/BJH, in vitro bioactivity test and the Cell viability assay were performed. The results show that cerium remains in the bioactive glass structure. The obtained material present in vitro bioactivity and promote the cell viability.Keywords: bioactive glass, bioactivity, cerium salt, material characterization, sol-gel method
Procedia PDF Downloads 2333082 Empirical and Indian Automotive Equity Portfolio Decision Support
Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu
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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.Keywords: Indian automotive sector, stock market decisions, equity portfolio analysis, decision tree classifiers, statistical data analysis
Procedia PDF Downloads 4853081 ANFIS Approach for Locating Faults in Underground Cables
Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat
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This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system. Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.Keywords: ANFIS, fault location, underground cable, wavelet transform
Procedia PDF Downloads 5133080 Microstructural and Tribological Properties of Thermally Sprayed High Entropy Alloys Coating
Authors: Abhijith N. V., Abhijit Pattnayak, Deepak Kumar
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Nowadays, a group of alloys, namely high entropy alloys (HEA), because of their excellent properties. However, the fabrication of HEAs requires multistage techniques, especially mill-ing, sieving, compaction, sintering, inert media, etc. These processes are laborious, costly, time-oriented, and unsuitable for commercial application. This study adopted a single-stage process-based HVOF thermal spray to develop HEA coating on SS304L substrates. The wear behavior of the deposited HEA coating was explored under different milling time durations (5h, 10h, and 15h, respectively). The effect of feedstock preparation, microstructure, surface chemistry, and mechanical and metallurgical properties on wear resistance was also investigated. The microstructure and composition of both coating and feedstock were evaluated by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis. Finally, the phase distribution was correlated by X-ray diffraction (XRD ) analysis. The results showed that 15h milled powder coating indicated better tribological than the base substrate and 5h,10h milled powder coating. A chemically stable Body Centered Cubic (BCC) solid solution phase was generated within the 15h milled powder-coated system, which resulted in superior tribological properties.Keywords: high entropy alloys coating, wear mechanism, HVOF coating, microstructure
Procedia PDF Downloads 983079 Predictive Modelling Approaches in Food Processing and Safety
Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary
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Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.Keywords: predictive modlleing, ann, ai, food
Procedia PDF Downloads 823078 Deep-Learning Based Approach to Facial Emotion Recognition through Convolutional Neural Network
Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah
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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.Keywords: CNN, deep-learning, facial emotion recognition, machine learning
Procedia PDF Downloads 953077 Probabilistic Approach to Contrast Theoretical Predictions from a Public Corruption Game Using Bayesian Networks
Authors: Jaime E. Fernandez, Pablo J. Valverde
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This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games
Procedia PDF Downloads 2103076 Pro-Ecological Antioxidants for Polymeric Composites
Authors: Masek A., Zaborski M.
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In our studies, we propose the use of natural, pro-ecological substances such as polyphenols to protect polymers against ageing. In our studies, we plan to focus on the following compounds: polyphenols, gallic acid esters, flavonoides, carotenoids, curcumin and its derivatives, vitamin A, tocochromanoles, betalain. Phyto-compounds will be selected on the basis of available literature and our preliminary studies. So, we will select compounds with various contents of hydroxyl groups and colored substances capable of participating in color oxidation processes. The natural antioxidants which were added to ethylene-octene elastomer (polyolefin elastomer-Engage) and ethylene-nonbornene (TOPAS). Composites were then subjected to numerous ageing: weathering (climat of Floryda), UV (0,7 W/m2), thermo-oxidation ageing (1000C/10days) and thermal-shock (-600C/+1000C) as a function of the aging time. The efficiency of used anti-ageing agents was checked on the base of the changes after the degradation in deformation energy (tensile strength and elongation at the break), cross-link density, color (parameters L,a,b) and values of carbonyl index (based on the spectrum of infra red spectroscopy), OIT (induction oxygen time as performed in using differential scanning calorimeter -DSC) of the vulcanizates. Therefore polyphenols are considered to be the best stabilisers for polymeric composites against to oxidation processes.Keywords: polymers, flavonoids, stabilization, ageing, oxidation
Procedia PDF Downloads 3073075 Strategies to Synthesize Ambient Stable Ultrathin Ag Film Supported on Oxide Substrate
Authors: Allamula Ashok, Peela Lasya, Daljin Jacob, P. Muhammed Razi, Satyesh Kumar Yadav
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We report zinc (Zn) as a seed layer material and a need for a specific disposition sequence to grow ultrathin silver (Ag) films on quartz (SiO₂). Ag films of thickness 4, 6, 8 and 10 nm were deposited by DC magnetron sputtering without and with Zn seed layer thickness of 1, 2 and 4 nm. The effect of Zn seed layer thickness and its annealing on the surface morphology, sheet resistance, and stability of ultrathin Ag films is investigated. We show that by increasing Zn seed layer thickness from 1 to 2 nm, there is a 5-order reduction in sheet resistance of 6 nm Ag films. We find that annealing of the seed layer is crucial to achieving stability of ultrathin Ag films. 6 nm Ag film with 2 nm Zn is unstable to 100 oC annealing, while the 6 nm Ag film with annealed 2 nm Zn seed layer is stable. 2 nm Zn seeded 8 nm Ag film maintained a constant sheet resistance of 7 Ω/□ for all 6 months of exposure to ambient conditions. Among the ultrathin film grown, 8nm Ag film with 2nm Zn seed layer had the best figure of merit with sheet resistance of 7 Ω/□, mean absolute surface roughness (Ra) ~1 nm, and optical transparency of 61 %. Such stable exposed ultrathin Ag films can find applications as catalysts, sensors, and transparent and conductive electrodes for solar cells, LEDs and plasmonic devices.Keywords: ultrathin Ag films, magnetron sputtering, thermal stability, seed layer, exposed silver, zinc.
Procedia PDF Downloads 393074 Biobased Polyurethane Derived from Transesterified Castor Oil: Synthesis and Charecterization
Authors: Sonalee Das, Smita Mohanty, S. K. Nayak
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Recent years has witnessed the increasing demand for natural resources and products in polyurethane synthesis because of global warming, sustainable development and oil crisis. For this purpose, different plant oils such as soybean oil, castor oil and linseed oil are extensively used. Moreover, the isocyanate used for the synthesis of polyurethane is derived from petroleum resources. In this present work attempts have been made for the successful synthesis of biobased isocyanate from castor oil with partially biobased isocyanate in presence of catalyst dibutyltin dilaurate (DBTDL). The goal of the present study was to investigate the thermal, mechanical, morphological and chemical properties of the synthesized polyurethane in terms of castor oil modification. The transesterified polyol shows broad and higher hydroxyl value as compared to castor oil which was confirmed by FTIR studies. The FTIR studies also revealed the successful synthesis of bio based polyurethane by showing characteristic peaks at 3300cm-1, 1715cm-1 and 1532cm-1 respectively. The TGA results showed three step degradation mechanism for the synthesized polyurethane from modified and unmodified castor oil. However, the modified polyurethane exhibited higher degradation temperature as compared to unmodified one. The mechanical properties also demonstrated higher tensile strength for modified polyurethane as compared to unmodified one.Keywords: castor oil, partially biobased Isocyanate, polyurethane synthesis, FTIR
Procedia PDF Downloads 3523073 Food Supply Chain Optimization: Achieving Cost Effectiveness Using Predictive Analytics
Authors: Jayant Kumar, Aarcha Jayachandran Sasikala, Barry Adrian Shepherd
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Public Distribution System is a flagship welfare programme of the Government of India with both historical and political significance. Targeted at lower sections of society,it is one of the largest supply chain networks in the world. There has been several studies by academics and planning commission about the effectiveness of the system. Our study focuses on applying predictive analytics to aid the central body to keep track of the problem of breach of service level agreement between the two echelons of food supply chain. Each shop breach is leading to a potential additional inventory carrying cost. Thus, through this study, we aim to show that aided with such analytics, the network can be made more cost effective. The methods we illustrate in this study are applicable to other commercial supply chains as well.Keywords: PDS, analytics, cost effectiveness, Karnataka, inventory cost, service level JEL classification: C53
Procedia PDF Downloads 533