Search results for: hybrid alkaline cements
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2250

Search results for: hybrid alkaline cements

720 Study on Accumulation of Heavy Metals in Sweet Potato, Grown in Industrially Polluted Regions

Authors: Violina Angelova, Galina Pevicharova

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A comparative research had been carried out to allow us to determine the quantities and the centers of accumulation of Pb, Cu, Zn and Cd in the vegetative and reproductive organs of the sweet potatoes and to ascertain the possibilities for growing them on soils, polluted with heavy metals. The experiments were performed on agricultural fields contaminated by the (1) Non-Ferrous-Metal Works near Plovdiv, (2) Lead and Zinc Complex near Kardjali and (3) a copper smelter near Pirdop, Bulgaria. The soils used in this experiment were characterized by acid, neutral and slightly alkaline reaction, loamy texture and a moderate content of organic matter. The total content of Zn, Pb, and Cd was high and exceeded the limit value in agriculture soils. Sweet potatoes were in a 2-year rotation scheme on three blocks in the experimental field. On reaching commercial ripeness the sweet potatoes were gathered and the contents of heavy metals in their different parts – root, tuber (peel and core), leaves and stems, were determined after microwave mineralization. The quantitative measurements were carried out with inductively coupled plasma atomic emission spectroscopy. The contamination of the sweet potatoes was due mainly to the presence of heavy metals in the soil, which entered the plants through their root system, as well as by diffusion through the peel. Pb, Cu, Zn, and Cd were selectively accumulated in the underground parts of the sweet potatoes, and most of all in the root system and the peel. Heavy metals have an impact on the development and productivity of the sweet potatoes. The high anthropogenic contamination leads to an increased assimilation of heavy metals which reduces the yield and the quality of the production of sweet potatoes, as well as leads to decrease of the absolute dry substance and the quantity of sugars in sweet potatoes. Sweet potatoes could be grown on soils, which are light to medium polluted with lead, zinc, and cadmium, as they do not accumulate these elements. On heavily polluted soils, however, (Pb – 1504 mg/kg, Zn – 3322 mg/kg, Cd – 47 mg/kg) the growing of sweet potatoes is not allowed, as the accumulation of Pb and Cd in the core of the potatoes exceeds the Maximum Acceptable Concentration. Acknowledgment: The authors gratefully acknowledge the financial support by the Bulgarian National Science Fund (Project DFNI DH04/9).

Keywords: heavy metals, polluted soils, sweet potatoes, uptake

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719 Integration of Multi Effect Desalination with Solid Oxide Fuel Cell/Gas Turbine Power Cycle

Authors: Mousa Meratizaman, Sina Monadizadeh, Majid Amidpour

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One of the most favorable thermal desalination methods used widely today is Multi Effect Desalination. High energy consumption in this method causes coupling it with high temperature power cycle like gas turbine. This combination leads to higher energy efficiency. One of the high temperature power systems which have cogeneration opportunities is Solid Oxide Fuel Cell / Gas Turbine. Integration of Multi Effect Desalination with Solid Oxide Fuel Cell /Gas Turbine power cycle in a range of 300-1000 kW is considered in this article. The exhausted heat of Solid Oxide Fuel Cell /Gas Turbine power cycle is used in Heat Recovery Steam Generator to produce needed motive steam for Desalination unit. Thermodynamic simulation and parametric studies of proposed system are carried out to investigate the system performance.

Keywords: solid oxide fuel cell, thermodynamic simulation, multi effect desalination, gas turbine hybrid cycle

Procedia PDF Downloads 379
718 Investigation of Dynamic Characteristic of Planetary Gear Set Based On Three-Axes Torque Measurement

Authors: Masao Nakagawa, Toshiki Hirogaki, Eiichi Aoyama, Mohamed Ali Ben Abbes

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A planetary gear set is widely used in hybrid vehicles as the power distribution system or in electric vehicles as the high reduction system, but due to its complexity with planet gears, its dynamic characteristic is not fully understood. There are many reports on two-axes driving or displacement of the planet gears under these conditions, but only few reports deal with three-axes driving. A three-axes driving condition is tested using three-axes torque measurement and focuses on the dynamic characteristic around the planet gears in this report. From experimental result, it was confirmed that the transition forces around the planet gears were balanced and the torques were also balanced around the instantaneous rotation center. The meshing frequency under these conditions was revealed to be the harmonics of two meshing frequencies; meshing frequency of the ring gear and that of the planet gears. The input power of the ring gear is distributed to the carrier and the sun gear in the dynamic sequential change of three fixed conditions; planet, star and solar modes.

Keywords: dynamic characteristic, gear, planetary gear set, torque measuring

Procedia PDF Downloads 381
717 Statistical Modeling of Constituents in Ash Evolved From Pulverized Coal Combustion

Authors: Esam Jassim

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Industries using conventional fossil fuels have an interest in better understanding the mechanism of particulate formation during combustion since such is responsible for emission of undesired inorganic elements that directly impact the atmospheric pollution level. Fine and ultrafine particulates have tendency to escape the flue gas cleaning devices to the atmosphere. They also preferentially collect on surfaces in power systems resulting in ascending in corrosion inclination, descending in the heat transfer thermal unit, and severe impact on human health. This adverseness manifests particularly in the regions of world where coal is the dominated source of energy for consumption. This study highlights the behavior of calcium transformation as mineral grains verses organically associated inorganic components during pulverized coal combustion. The influence of existing type of calcium on the coarse, fine and ultrafine mode formation mechanisms is also presented. The impact of two sub-bituminous coals on particle size and calcium composition evolution during combustion is to be assessed. Three mixed blends named Blends 1, 2, and 3 are selected according to the ration of coal A to coal B by weight. Calcium percentage in original coal increases as going from Blend 1 to 3. A mathematical model and a new approach of describing constituent distribution are proposed. Analysis of experiments of calcium distribution in ash is also modeled using Poisson distribution. A novel parameter, called elemental index λ, is introduced as a measuring factor of element distribution. Results show that calcium in ash that originally in coal as mineral grains has index of 17, whereas organically associated calcium transformed to fly ash shown to be best described when elemental index λ is 7. As an alkaline-earth element, calcium is considered the fundamental element responsible for boiler deficiency since it is the major player in the mechanism of ash slagging process. The mechanism of particle size distribution and mineral species of ash particles are presented using CCSEM and size-segregated ash characteristics. Conclusions are drawn from the analysis of pulverized coal ash generated from a utility-scale boiler.

Keywords: coal combustion, inorganic element, calcium evolution, fluid dynamics

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716 Proprotein Convertase Subtilisin/Kexin Type 9 Enhances Arterial Medial Calcification in a Uremic Rat Model of Chronic Kidney Disease

Authors: Maria Giovanna Lupo, Marina Camera, Marcello Rattazzi, Nicola Ferri

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A complex interplay among chronic kidney disease, lipid metabolism and aortic calcification has been recognized starting from results of many clinical and experimental studies. Here we investigated the influence of kidney function on PCSK9 levels, both in uremic rats and in clinical observation study, and its potential direct action on cultured smooth muscle cells (SMCs) calcification. In a cohort of 594 subjects enrolled in a single centre, observational, cross-sectional and longitudinal study, a negative association between GFR and plasma PCSK9 was found. Atherosclerotic cardiovascular disease (ASCVD), as co-morbidity, further increased PCSK9 plasma levels. Diet-induced uremic condition in rats, induced aortic calcification and increased total cholesterol and PCSK9 levels in plasma, livers and kidneys. Immunohistochemical analysis confirmed PCSK9 expression in aortic SMCs. SMCs overexpressing PCSK9 (SMCsPCSK9), cultured for 7-days in a pro-calcification environment (2.0mM or 2.4mM inorganic phosphate, Pi) showed a significantly higher extracellular calcium (Ca2+) deposition compared to mocked SMCs. Under the same experimental conditions, the addition of exogenous recombinant PCSK9 did not increase the extracellular calcification of SMCs. By flow cytometry analysis we showed that SMCsPCSK9, in response to 2.4mM Pi, released higher number of extracellular vesicles (EVs) positive for three tetraspanin molecules, such as CD63, CD9, and CD81. EVs derived from SMCsPCSK9 tended to be more enriched in calcium and alkaline phosphatase (ALPL), compared to EVs from mocks SMCs. In conclusion, our study reveals a direct role of PCSK9 on vascular calcification induced by higher inorganic phosphate levels associated to CKD condition. This effect appears to be mediated by a positive effect of endogenous PCSK9 on the release of EVs containing Ca2+ and ALP, which facilitate the deposition inorganic calcium phosphate crystals.

Keywords: PCSK9, calcification, extracellular vesicles, chronic kidney disease

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715 A Novel Application of CORDYCEPIN (Cordycepssinensis Extract): Maintaining Stem Cell Pluripotency and Improving iPS Generation Efficiency

Authors: Shih-Ping Liu, Cheng-Hsuan Chang, Yu-Chuen Huang, Shih-Yin Chen, Woei-Cherng Shyu

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Embryonic stem cells (ES) and induced pluripotnet stem cells (iPS) are both pluripotent stem cells. For mouse stem cells culture technology, leukemia inhibitory factor (LIF) was used to maintain the pluripotency of stem cells in vitro. However, LIF is an expensive reagent. The goal of this study was to find out a pure compound extracted from Chinese herbal medicine that could maintain stem cells pluripotency to replace LIF and improve the iPS generation efficiency. From 20 candidates traditional Chinese medicine we found that Cordycepsmilitaris triggered the up-regulation of stem cells activating genes (Oct4 and Sox2) expression levels in MEF cells. Cordycepin, a major active component of Cordycepsmilitaris, also could up-regulate Oct4 and Sox2 gene expression. Furthermore, we used ES and iPS cells and treated them with different concentrations of Cordycepin (replaced LIF in the culture medium) to test whether it was useful to maintain the pluripotency. The results showed higher expression levels of several stem cells markers in 10 μM Cordycepin-treated ES and iPS cells compared to controls that did not contain LIF, including alkaline phosphatase, SSEA1, and Nanog. Embryonic body formation and differentiation confirmed that 10 μM Cordycepin-containing medium was capable to maintain stem cells pluripotency after four times passages. For mechanism analysis, microarray analysis indicated extracellular matrix and Jak/Stat signaling pathway as the top two deregulated pathways. In ECM pathway, we determined that the integrin αVβ5 expression levels and phosphorylated Src levels increased after Cordycepin treatment. In addition, the phosphorylated Jak2 and phosphorylated Sat3 protein levels were increased after Cordycepin treatment and suppressed with the Jak2 inhibitor, AG490. The expression of cytokines associated with Jak2/Stat3 signaling pathway were also up-regulated by Q-PCR and ELISA assay. Lastly, we used Oct4-GFP MEF cells to test iPS generation efficiency following Cordycepin treatment. We observed that 10 Μm Cordycepin significantly increased the iPS generation efficiency in day 21. In conclusion, we demonstrated Cordycepin could maintain the pluripotency of stem cells through both of ECM and Jak2/Stat3 signaling pathway and improved iPS generation efficiency.

Keywords: cordycepin, iPS cells, Jak2/Stat3 signaling pathway, molecular biology

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714 Aquafaba Derived from Korean Soybean Cultivars: A Novel Vegan Egg Replacer

Authors: Yue He, Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin J. T. Reaney

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Recently, pulse cooking water (a.k.a. Aquafaba) has been used as an important and cost-effective alternative to eggs in gluten-free, vegan cooking and baking applications. The aquafaba (AQ) is primarily due to its excellent ability to stabilize foams and emulsions in foods. However, the functional ingredients of this excellent AQ are usually discarded with the compound release. This study developed a high-functional food material, AQ, using functional soybean AQ that has not been studied in Korea. A zero-waste and cost-effective hybrid process were used to produce oil emulsifiers from Korean soybeans. The treatment technique was implemented using a small number of efficient steps. Aquafaba from Backtae had the best emulsion properties (92%) and has the potential to produce more stable food oil emulsions. Therefore, this study is expected to be utilized in the development of the first gluten-free, vegan product for vegetarians and consumers with animal protein allergies, utilizing wastewater from cooked soybeans as a source of plant protein that can replace animal protein.

Keywords: aquafaba, soybean, chickpea, emulsifiers, egg replacer, egg-free products

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713 Evolution of Fashion Design in the Era of High-Tech Culture

Authors: Galina Mihaleva, C. Koh

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Fashion, like many other design fields, undergoes numerous evolutions throughout the ages. This paper aims to recognize and evaluate the significance of advance technology in fashion design and examine how it changes the role of modern fashion designers by modifying the creation process. It also touches on how modern culture is involved in such developments and how it affects fashion design in terms of conceptualizing and fabrication. The methodology used is through surveying the various examples of technological applications to fashion design and drawing parallels between what was achievable then and what is achievable now. By comparing case studies, existing fashion design examples and crafting method experimentations; we then spot patterns in which to predict the direction of future developments in the field. A breakdown on the elements of technology in fashion design helps us understand the driving force behind such a trend. The results from explorations in the paper have shown that there is an observed pattern of a distinct increase in interest and progress in the field of fashion technology, which leads to the birth of hybrid crafting methods. In conclusion, it is shown that as fashion technology continues to evolve, their role in clothing crafting becomes more prominent and grows far beyond the humble sewing machine.

Keywords: fashion design, functional aesthetics, smart textiles, 3D printing

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712 A Gyro-stabilized Autonomous Multi-terrain Quadrupedal-wheeled Robot: Towards Edge-enabled Self-balancing, Autonomy, and Terramechanical Efficiency of Unmanned Off-road Vehicles

Authors: Mbadiwe S. Benyeogor, Oladayo O. Olakanmi, Kosisochukwu P. Nnoli, Olusegun I. Lawal, Eric JJ. Gratton

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For a robot or any vehicular system to navigate in off-road terrain, its driving mechanisms and the electro-software system must be capable of generating, controlling, and moderating sufficient mechanical power with precision. This paper proposes an autonomous robot with a gyro-stabilized active suspension system in form of a hybrid quadrupedal wheel drive mechanism. This system is to serve as a miniature model for demonstrating how off-road vehicles can be robotized into efficient terramechanical mobile platforms that are capable of self-balanced autonomous navigation and maneuvering on rough and uneven topographies. Results from tests and analysis show that the developed system performs as expected. Therefore, our model and control devices can be adapted to computerizing, automating, and upgrading the operation of unmanned ground vehicles for off-road navigation.

Keywords: active suspension, autonomous robots, edge computing, navigational sensors, terramechanics

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711 Construction of a Supply Chain Model Using the PREVA Method: The Case of Innovative Sargasso Recovery Projects in Ther Lesser Antilles

Authors: Maurice Bilioniere, Katie Lanneau

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Suddenly appeared in 2011, invasions of sargasso seaweeds Fluitans and Natans are a climatic hazard which causes many problems in the Caribbean. Faced with the growth and frequency of the phenomenon of massive sargasso stranding on their coasts, the French West Indies are moving towards the path of industrial recovery. In this context of innovative projects, we will analyze the necessary requirements for the management and performance of the supply chain, taking into account the observed volatility of the sargasso input. Our prospective approach will consist in studying the theoretical framework of modeling a hybrid supply chain by coupling the discreet event simulation (DES) with a valuation of the process costs according to the "activity-based costing" method (ABC). The PREVA approach (PRocess EVAluation) chosen for our modeling has the advantage of evaluating the financial flows of the logistic process using an analytical model chained with an action model for the evaluation or optimization of physical flows.

Keywords: sargasso, PREVA modeling, supply chain, ABC method, discreet event simulation (DES)

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710 Utilization and Proximate Composition of Nile Tilapia, Common Carp and African Mudfish Polycultured in Fertilized Ponds

Authors: I. A. Yola

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Impact of poultry dropping, cow dung and rumen content on utilization and proximate composition of Oreochromis niliticus, Clarias gariepinus and Cyprinus capio in a polyculture system were studied. The research was conducted over a period of 52 weeks. Poultry droppings (PD), cow dung (CD) and rumen content (RC) were applied at three levels 30g,60g and 120g/m2/week, 25g,50g and 100g/m2/week and 22g, 44g and 88g/m2/week treatment, respectively. The control only conventional feed with 40% CP without manure application was used. Physicochemical and biological properties measured were higher in manure pond than control. The difference was statistically significant (P < 0.05) between and within treatments with exception of temperature with a combined mean of 27.900C. The water was consistently alkaline with mean values for pH of 6.61, transparency 22.6cm, conductivity 35.00µhos/cm, dissolved oxygen 4.6 mg/l, biological oxygen demand 2.8mg/l, nitrate and phosphates 0.9mg/l and 0.35mg/l, respectively. The three fish species increase in weight with increased manure rate, with a higher value in PD treatment on C. capio record 340g, O. niloticus weighed 310g and C. gariepinus 280g over the experimental period. Fishes fed supplementary diet (control) grew bigger with highest value on C. capio (685g) O. niloticus (620g) and then C. gariepinus (526g). The differences were statistically significant (P < 0.05). The result of whole body proximate analysis indicated that various manures and rates had an irregular pattern on the protein and ash gain per 100g of fish body weight gain. The combined means for whole fish carcass protein, lipids, moisture, ash and gross energy were 11.84, 2.43, 74.63, 3.00 and 109.9 respectively. The notable exceptions were significant (p < 0.05) increases in body fat and gross energy gains in all fish species accompanied by decreases in percentages of moisture as manure rates increased. Survival percentage decreases from 80% to 70%. It is recommended to use poultry dropping as manure/feeds at the rate of 120kg/ha/week for good performances in polyculture.

Keywords: organic manure, Nile tilapia, African mud fish, common carp, proximate composition

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709 A Hybrid Digital Watermarking Scheme

Authors: Nazish Saleem Abbas, Muhammad Haris Jamil, Hamid Sharif

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Digital watermarking is a technique that allows an individual to add and hide secret information, copyright notice, or other verification message inside a digital audio, video, or image. Today, with the advancement of technology, modern healthcare systems manage patients’ diagnostic information in a digital way in many countries. When transmitted between hospitals through the internet, the medical data becomes vulnerable to attacks and requires security and confidentiality. Digital watermarking techniques are used in order to ensure the authenticity, security and management of medical images and related information. This paper proposes a watermarking technique that embeds a watermark in medical images imperceptibly and securely. In this work, digital watermarking on medical images is carried out using the Least Significant Bit (LSB) with the Discrete Cosine Transform (DCT). The proposed methods of embedding and extraction of a watermark in a watermarked image are performed in the frequency domain using LSB by XOR operation. The quality of the watermarked medical image is measured by the Peak signal-to-noise ratio (PSNR). It was observed that the watermarked medical image obtained performing XOR operation between DCT and LSB survived compression attack having a PSNR up to 38.98.

Keywords: watermarking, image processing, DCT, LSB, PSNR

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708 Lowering Error Floors by Concatenation of Low-Density Parity-Check and Array Code

Authors: Cinna Soltanpur, Mohammad Ghamari, Behzad Momahed Heravi, Fatemeh Zare

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Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss.

Keywords: concatenated coding, low–density parity–check codes, array code, error floors

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707 Relation between Physical and Mechanical Properties of Concrete Paving Stones Using Neuro-Fuzzy Approach

Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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706 Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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705 Sentiment Analysis of Ensemble-Based Classifiers for E-Mail Data

Authors: Muthukumarasamy Govindarajan

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Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

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704 Modeling User Context Using CEAR Diagram

Authors: Ravindra Dastikop, G. S. Thyagaraju, U. P. Kulkarni

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Even though the number of context aware applications is increasing day by day along with the users, till today there is no generic programming paradigm for context aware applications. This situation could be remedied by design and developing the appropriate context modeling and programming paradigm for context aware applications. In this paper, we are proposing the static context model and metrics for validating the expressiveness and understandability of the model. The proposed context modeling is a way of describing a situation of user using context entities , attributes and relationships .The model which is an extended and hybrid version of ER model, ontology model and Graphical model is specifically meant for expressing and understanding the user situation in context aware environment. The model is useful for understanding context aware problems, preparing documentation and designing programs and databases. The model makes use of context entity attributes relationship (CEAR) diagram for representation of association between the context entities and attributes. We have identified a new set of graphical notations for improving the expressiveness and understandability of context from the end user perspective .

Keywords: user context, context entity, context entity attributes, situation, sensors, devices, relationships, actors, expressiveness, understandability

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703 Design and Analysis of a Laminated Composite Automotive Drive Shaft

Authors: Hossein Kh. Bisheh, Nan Wu

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Advanced composite materials have a great importance in engineering structures due to their high specific modulus and strength and low weight. These materials can be used in design and fabrication of automotive drive shafts to reduce the weight of the structure. Hence, an optimum design of a composite drive shaft satisfying the design criteria, can be an appropriate substitution of metallic drive shafts. The aim of this study is to design and analyze a composite automotive drive shaft with high specific strength and low weight satisfying the design criteria. Tsai-Wu criterion is chosen as the failure criterion. Various designs with different lay-ups and materials are investigated based on the design requirements and finally, an optimum design satisfying the design criteria is chosen based on the weight and cost considerations. The results of this study indicate that if the weight is the main concern, a shaft made of Carbon/Epoxy can be a good option, and if the cost is a more important parameter, a hybrid shaft made of aluminum and Carbon/Epoxy can be considered.

Keywords: Bending natural frequency, Composite drive shaft, Peak torque, Torsional buckling

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702 Study of Electrical Properties of An-Fl Based Organic Semiconducting Thin Film

Authors: A.G. S. Aldajani, N. Smida, M. G. Althobaiti, B. Zaidi

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In order to exploit the good electrical properties of anthracene and the excellent properties of fluorescein, new hybrid material has been synthesized (An-Fl). Current-voltage measurements were done on a new single-layer ITO/An-FL/Al device of typically 100 nm thickness. Atypical diode behavior is observed with a turn-on voltage of 4.4 V, a dynamic resistance of 74.07 KΩ and a rectification ratio of 2.02 due to unbalanced transport. Results show also that the current-voltage characteristics present three different regimes of the power-law (J~Vᵐ) for which the conduction mechanism is well described with space-charge-limited current conduction mechanism (SCLC) with a charge carrier mobility of 2.38.10⁻⁵cm2V⁻¹S⁻¹. Moreover, the electrical transport properties of this device have been carried out using a dependent frequency study in the range (50 Hz–1.4 MHz) for different applied biases (from 0 to 6 V). At lower frequency, the σdc values increase with bias voltage rising, supporting that the mobile ion can hop successfully to its nearest vacant site. From σac and impedance measurements, the equivalent electrical circuit is evidenced, where the conductivity process is coherent with an exponential trap distribution caused by structural defects and/or chemical impurities.

Keywords: semiconducting polymer, conductivity, SCLC, impedance spectroscopy

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701 Machine Learning Methods for Flood Hazard Mapping

Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

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This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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700 Multichannel Scheme under Fairness Environment for Cognitive Radio Networks

Authors: Hans Marquez Ramos, Cesar Hernandez, Ingrid Páez

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This paper develops a multiple channel assignment model, which allows to take advantage in most efficient way, spectrum opportunities in cognitive radio networks. Developed scheme allows make several available and frequency adjacent channel assignments, which require a bigger wide band, under an equality environment. The hybrid assignment model it is made by to algorithms, one who makes the ranking and select available frequency channels and the other one in charge of establishing an equality criteria, in order to not restrict spectrum opportunities for all other secondary users who wish to make transmissions. Measurements made were done for average bandwidth, average delay, as well fairness computation for several channel assignment. Reached results were evaluated with experimental spectrum occupational data from GSM frequency band captured. Developed model, shows evidence of improvement in spectrum opportunity use and a wider average transmit bandwidth for each secondary user, maintaining equality criteria in channel assignment.

Keywords: bandwidth, fairness, multichannel, secondary users

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699 Machine Learning Approach for Automating Electronic Component Error Classification and Detection

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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698 Origins of Chicago Common Brick: Examining a Masonry Shell Encasing a New Ando Museum

Authors: Daniel Joseph Whittaker

Abstract:

This paper examines the broad array of historic sites from which Chicago common brick has emerged, and the methods this brick has been utilized within and around a new hybrid structure recently completed-and periodically opened to the public, as a private art, architecture, design, and social activism gallery space. Various technical aspects regarding the structural and aesthetic reuse methods of salvaged brick within the interior and exterior of this new Tadao Ando-designed building in Lincoln Park, Chicago, are explored. This paper expands specifically upon the multiple possible origins of Chicago common brick, as well as the extant brick currently composing the surrounding alley which is integral to demarcating the southern site boundary of the old apartment building now gallery. Themes encompassing Chicago’s archeological and architectural history, local resource extraction, and labor practices permeate this paper’s investigation into urban, social and architectural history and building construction technology advancements through time.

Keywords: masonry construction, history brickmaking, private museums, Chicago Illinois, Tadao Ando

Procedia PDF Downloads 171
697 Influence of Magnetic Bio-Stimulation Effects on Pre-Sown Hybrid Sunflower Seeds Germination, Growth, and on the Percentage of Antioxidant Activities

Authors: Nighat Zia-ud-Den, Shazia Anwer Bukhari

Abstract:

In the present study, sunflower seeds were exposed to magnetic bio-stimulation at different milli Tesla, and their effects were studied. The present study addressed to establish the effectiveness of magnetic bio-stimulation on seed germination, growth, and other dynamics of crop growth. The changes in physiological characters, i.e. the growth parameters of seedlings (biomass, root and shoot length, fresh and dry weight of root shoot leaf and fruit, leaf area, the height of plants, number of leaves, and number of fruits per plant) and antioxidant activities were measured. The parameters related to germination and growth were measured under controlled conditions while they changed significantly compared with that of the control. These changes suggested that magnetic seed stimulator enhanced the inner energy of seeds, which contributed to the acceleration of the growth and development of seedlings. Moreover, pretreatment with a magnetic field was found to be a positive impact on sunflower seeds germination, growth, and other biochemical parameters.

Keywords: sunflower seeds, physical priming method, biochemical parameters, antioxidant activities

Procedia PDF Downloads 164
696 An Overview on Aluminum Matrix Composites: Liquid State Processing

Authors: S. P. Jordan, G. Christian, S. P. Jeffs

Abstract:

Modern composite materials are increasingly being chosen in replacement of heavier metallic material systems within many engineering fields including aerospace and automotive industries. The increasing push towards satisfying environmental targets are fuelling new material technologies and manufacturing processes. This paper will introduce materials and manufacturing processes using metal matrix composites along with manufacturing processes optimized at Alvant Ltd., based in Basingstoke in the UK which offers modern, cost effective, selectively reinforced composites for light-weighting applications within engineering. An overview and introduction into modern optimized manufacturing methods capable of producing viable replacements for heavier metallic and lower temperature capable polymer composites are offered. A review of the capabilities and future applications of this viable material is discussed to highlight the potential involved in further optimization of old manufacturing techniques, to fully realize the potential to lightweight material using cost-effective methods.

Keywords: aluminium matrix composites, light-weighting, hybrid squeeze casting, strategically placed reinforcements

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695 The Transport of Radical Species to Single and Double Strand Breaks in the Liver’s DNA Molecule by a Hybrid Method of Type Monte Carlo - Diffusion Equation

Authors: H. Oudira, A. Saifi

Abstract:

The therapeutic utility of certain Auger emitters such as iodine-125 depends on their position within the cell nucleus . Or diagnostically, and to maintain as low as possible cell damage, it is preferable to have radionuclide localized outside the cell or at least the core. One solution to this problem is to consider markers capable of conveying anticancer drugs to the tumor site regardless of their location within the human body. The objective of this study is to simulate the impact of a complex such as bleomycin on single and double strand breaks in the DNA molecule. Indeed, this simulation consists of the following transactions: - Construction of BLM -Fe- DNA complex. - Simulation of the electron’s transport from the metastable state excitation of Fe 57 by the Monte Carlo method. - Treatment of chemical reactions in the considered environment by the diffusion equation. For physical, physico-chemical and finally chemical steps, the geometry of the complex is considered as a sphere of 50 nm centered on the binding site , and the mathematical method used is called step by step based on Monte Carlo codes.

Keywords: concentration, yield, radical species, bleomycin, excitation, DNA

Procedia PDF Downloads 457
694 Optimal Solutions for Real-Time Scheduling of Reconfigurable Embedded Systems Based on Neural Networks with Minimization of Power Consumption

Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

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In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

Procedia PDF Downloads 371
693 Short Term Distribution Load Forecasting Using Wavelet Transform and Artificial Neural Networks

Authors: S. Neelima, P. S. Subramanyam

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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

Procedia PDF Downloads 436
692 Comparison of Methods for Detecting and Quantifying Amplitude Modulation of Wind Farm Noise

Authors: Phuc D. Nguyen, Kristy L. Hansen, Branko Zajamsek

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The existence of special characteristics of wind farm noise such as amplitude modulation (AM) contributes significantly to annoyance, which could ultimately result in sleep disturbance and other adverse health effects for residents living near wind farms. In order to detect and quantify this phenomenon, several methods have been developed which can be separated into three types: time-domain, frequency-domain and hybrid methods. However, due to a lack of systematic validation of these methods, it is still difficult to select the best method for identifying AM. Furthermore, previous comparisons between AM methods have been predominantly qualitative or based on synthesised signals, which are not representative of the actual noise. In this study, a comparison between methods for detecting and quantifying AM has been carried out. The results are based on analysis of real noise data which were measured at a wind farm in South Australia. In order to evaluate the performance of these methods in terms of detecting AM, an approach has been developed to select the most successful method of AM detection. This approach uses a receiver operating characteristic (ROC) curve which is based on detection of AM in audio files by experts.

Keywords: amplitude modulation, wind farm noise, ROC curve

Procedia PDF Downloads 145
691 5G Future Hyper-Dense Networks: An Empirical Study and Standardization Challenges

Authors: W. Hashim, H. Burok, N. Ghazaly, H. Ahmad Nasir, N. Mohamad Anas, A. F. Ismail, K. L. Yau

Abstract:

Future communication networks require devices that are able to work on a single platform but support heterogeneous operations which lead to service diversity and functional flexibility. This paper proposes two cognitive mechanisms termed cognitive hybrid function which is applied in multiple broadband user terminals in order to maintain reliable connectivity and preventing unnecessary interferences. By employing such mechanisms especially for future hyper-dense network, we can observe their performances in terms of optimized speed and power saving efficiency. Results were obtained from several empirical laboratory studies. It was found that selecting reliable network had shown a better optimized speed performance up to 37% improvement as compared without such function. In terms of power adjustment, our evaluation of this mechanism can reduce the power to 5dB while maintaining the same level of throughput at higher power performance. We also discuss the issues impacting future telecommunication standards whenever such devices get in place.

Keywords: dense network, intelligent network selection, multiple networks, transmit power adjustment

Procedia PDF Downloads 376