Search results for: modified simplex algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5894

Search results for: modified simplex algorithm

4814 An AI-Based Dynamical Resource Allocation Calculation Algorithm for Unmanned Aerial Vehicle

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

Procedia PDF Downloads 112
4813 Evaluation of Modified Asphalt Mixture with Hospital Spun-Bond Waste for Enhanced Crack Resistance

Authors: Ziba Talaeizadeh, Taghi Ebadi

Abstract:

Hospitals and medical centers generate a wide array of infectious waste on a daily basis, leading to pressing environmental concerns associated with proper disposal. Disposable plastic items and spun-bond clothing, commonly made from polypropylene, pose a significant risk of disease transmission, necessitating specialized waste management strategies. Incorporating these materials into bituminous asphalt production offers a potential solution, as it can modify asphalt mixtures and reduce susceptibility to cracking. This study aims to assess the crack resistance of asphalt mixtures modified with hospital spun-bond waste. Asphalt mixtures were prepared using the Marshall method, with spun-bond waste added in varying proportions (5% to 20%). The Semi-Circular Bending (SCB) test was conducted to evaluate asphalt fracture behavior under Mode I loading at controlled speeds of 5, 20, and 50 millimeters per minute and an average temperature of 25°C. Parameters such as fracture energy (FE) and Crack Resistance Index (CRI) were quantified. The results indicate that the addition of 10% to 15% spun-bond polypropylene polymer enhances the performance of the modified mixture, resulting in an 18% increase in fracture energy and an 11% reduction in cracking stiffness compared to the control sample. Further investigations involving factors like compaction level, bitumen type, and aggregate grading are recommended to address medical waste management and mitigate asphalt pavement cracking issues.

Keywords: asphalt cracking, hospital waste, semi-circular bending test, spun-bond

Procedia PDF Downloads 61
4812 Subband Coding and Glottal Closure Instant (GCI) Using SEDREAMS Algorithm

Authors: Harisudha Kuresan, Dhanalakshmi Samiappan, T. Rama Rao

Abstract:

In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm.

Keywords: SEDREAMS, GCI, SBC, GOI

Procedia PDF Downloads 358
4811 Multi-Objective Random Drift Particle Swarm Optimization Algorithm Based on RDPSO and Crowding Distance Sorting

Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

Abstract:

In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

Procedia PDF Downloads 255
4810 Synthesis and Characterization of Recycled Isotactic Polypropylene Nanocomposites Containing Date Wood Fiber

Authors: Habib Shaban

Abstract:

Nanocomposites of isotactic polypropylene (iPP) and date wood fiber were prepared after modification of the host matrix by reactive extrusion grafting of maleic anhydride. Chemical and mechanical treatment of date wood flour (WF) was conducted to obtain nanocrystalline cellulose. Layered silicates (clay) were partially intercalated with date wood fiber, and the modified layered silicate was used as filler in the PP matrix via a melt-blending process. The tensile strength of composites prepared from wood fiber modified clay was greater than that of the iPP-clay and iPP-WF composites at a 6% filler concentration, whereas deterioration of mechanical properties was observed when clay and WF were used alone for reinforcement. The dispersion of the filler in the matrix significantly decreased after clay modification with cellulose at higher concentrations, as shown by X-ray diffraction (XRD) data.

Keywords: nanocomposites, isotactic polypropylene, date wood flour, intercalated, melt-blending

Procedia PDF Downloads 386
4809 Nanomechanical Characterization of Titanium Alloy Modified by Nitrogen Ion Implantation

Authors: Josef Sepitka, Petr Vlcak, Tomas Horazdovsky, Vratislav Perina

Abstract:

An ion implantation technique was used for designing the surface area of a titanium alloy and for irradiation-enhanced hardening of the surface. The Ti6Al4V alloy was treated by nitrogen ion implantation at fluences of 2·1017 and 4·1017 cm-2 and at ion energy 90 keV. The depth distribution of the nitrogen was investigated by Rutherford Backscattering Spectroscopy. The gradient of mechanical properties was investigated by nanoindentation. The continuous measurement mode was used to obtain depth profiles of the indentation hardness and the reduced storage modulus of the modified surface area. The reduced storage modulus and the hardness increase with increasing fluence. Increased fluence shifts the peak of the mechanical properties as well as the peak of nitrogen concentration towards to the surface. This effect suggests a direct relationship between mechanical properties and nitrogen distribution.

Keywords: nitrogen ion implantation, titanium-based nanolayer, storage modulus, hardness, microstructure

Procedia PDF Downloads 343
4808 An End-to-end Piping and Instrumentation Diagram Information Recognition System

Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

Abstract:

Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

Procedia PDF Downloads 153
4807 Global Optimization: The Alienor Method Mixed with Piyavskii-Shubert Technique

Authors: Guettal Djaouida, Ziadi Abdelkader

Abstract:

In this paper, we study a coupling of the Alienor method with the algorithm of Piyavskii-Shubert. The classical multidimensional global optimization methods involves great difficulties for their implementation to high dimensions. The Alienor method allows to transform a multivariable function into a function of a single variable for which it is possible to use efficient and rapid method for calculating the the global optimum. This simplification is based on the using of a reducing transformation called Alienor.

Keywords: global optimization, reducing transformation, α-dense curves, Alienor method, Piyavskii-Shubert algorithm

Procedia PDF Downloads 503
4806 2D-Modeling with Lego Mindstorms

Authors: Miroslav Popelka, Jakub Nozicka

Abstract:

The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software

Procedia PDF Downloads 473
4805 Optimal Capacitor Placement in Distribution Using Cuckoo Optimization Algorithm

Authors: Ali Ravangard, S. Mohammadi

Abstract:

Shunt Capacitors have several uses in the electric power systems. They are utilized as sources of reactive power by connecting them in line-to-neutral. Electric utilities have also connected capacitors in series with long lines in order to reduce its impedance. This is particularly common in the transmission level, where the lines have length in several hundreds of kilometers. However, this post will generally discuss shunt capacitors. In distribution systems, shunt capacitors are used to reduce power losses, to improve voltage profile, and to increase the maximum flow through cables and transformers. This paper presents a new method to determine the optimal locations and economical sizing of fixed and/or switched shunt capacitors with a view to power losses reduction and voltage stability enhancement. For solving the problem, a new enhanced cuckoo optimization algorithm is presented.The proposed method is tested on distribution test system and the results show that the algorithm suitable for practical implementation on real systems with any size.

Keywords: capacitor placement, power losses, voltage stability, radial distribution systems

Procedia PDF Downloads 377
4804 A 5G Architecture Based to Dynamic Vehicular Clustering Enhancing VoD Services Over Vehicular Ad hoc Networks

Authors: Lamaa Sellami, Bechir Alaya

Abstract:

Nowadays, video-on-demand (VoD) applications are becoming one of the tendencies driving vehicular network users. In this paper, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different cars included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over VANET. The proposed algorithm takes advantage of the concept of small cells and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)- Advanced network. The proposed clustering algorithm considers multiple characteristics such as the vehicle’s position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.

Keywords: video-on-demand, vehicular ad-hoc network, mobility, vehicular traffic load, small cell, wireless backhaul, LTE-advanced, latency, packet loss

Procedia PDF Downloads 142
4803 A Character Detection Method for Ancient Yi Books Based on Connected Components and Regressive Character Segmentation

Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

Abstract:

Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

Procedia PDF Downloads 132
4802 An Approach to the Assembly Line Balancing Problem with Uncertain Operation Time

Authors: Zhongmin Wang, Lin Wei, Hengshan Zhang, Tianhua Chen, Yimin Zhou

Abstract:

The assembly line balancing problems are signficant in mass production systems. In order to deal with the uncertainties that practically exist but barely mentioned in the literature, this paper develops a mathematic model with an optimisation algorithm to solve the assembly line balancing problem with uncertainty operation time. The developed model is able to work with a variable number of workstations under the uncertain environment, aiming to obtain the minimal number of workstation and minimal idle time for each workstation. In particular, the proposed approach first introduces the concept of protection time that closely works with the uncertain operation time. Four dominance rules and the mechanism of determining up and low bounds are subsequently put forward, which serve as the basis for the proposed branch and bound algorithm. Experimental results show that the proposed work verified on a benchmark data set is able to solve the uncertainties efficiently.

Keywords: assembly lines, SALBP-UOT, uncertain operation time, branch and bound algorithm.

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4801 An Algorithm for Preventing the Irregular Operation Modes of the Drive Synchronous Motor Providing the Ore Grinding

Authors: Baghdasaryan Marinka

Abstract:

The current scientific and engineering interest concerning the problems of preventing the emergency manifestations of drive synchronous motors, ensuring the ore grinding technological process has been justified. The analysis of the known works devoted to the abnormal operation modes of synchronous motors and possibilities of protection against them, has shown that their application is inexpedient for preventing the impermissible displays arising in the electrical drive synchronous motors ensuring the ore-grinding process. The main energy and technological factors affecting the technical condition of synchronous motors are evaluated. An algorithm for preventing the irregular operation modes of the electrical drive synchronous motor applied in the ore-grinding technological process has been developed and proposed for further application which gives an opportunity to provide smart solutions, ensuring the safe operation of the drive synchronous motor by a comprehensive consideration of the energy and technological factors.

Keywords: synchronous motor, abnormal operating mode, electric drive, algorithm, energy factor, technological factor

Procedia PDF Downloads 137
4800 Efficient Reconstruction of DNA Distance Matrices Using an Inverse Problem Approach

Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

Abstract:

We continue to consider one of the cybernetic methods in computational biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the not fully filled distance matrix of DNA chains. When applied in a programming context, it is revealed that with a modern computer of average capabilities, creating even a small-sized distance matrix for mitochondrial DNA sequences is quite time-consuming with standard algorithms. As the size of the matrix grows larger, the computational effort required increases significantly, potentially spanning several weeks to months of non-stop computer processing. Hence, calculating the distance matrix on conventional computers is hardly feasible, and supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains; then, we published algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. In this paper, we propose an algorithm for restoring the distance matrix for DNA chains, and the primary focus is on enhancing the algorithms that shape the greedy function within the branches and boundaries method framework.

Keywords: DNA chains, distance matrix, optimization problem, restoring algorithm, greedy algorithm, heuristics

Procedia PDF Downloads 119
4799 Spectral Clustering for Manufacturing Cell Formation

Authors: Yessica Nataliani, Miin-Shen Yang

Abstract:

Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices.

Keywords: group technology, cell formation, spectral clustering, grouping efficiency

Procedia PDF Downloads 408
4798 Control of a Quadcopter Using Genetic Algorithm Methods

Authors: Mostafa Mjahed

Abstract:

This paper concerns the control of a nonlinear system using two different methods, reference model and genetic algorithm. The quadcopter is a nonlinear unstable system, which is a part of aerial robots. It is constituted by four rotors placed at the end of a cross. The center of this cross is occupied by the control circuit. Its motions are governed by six degrees of freedom: three rotations around 3 axes (roll, pitch and yaw) and the three spatial translations. The control of such system is complex, because of nonlinearity of its dynamic representation and the number of parameters, which it involves. Numerous studies have been developed to model and stabilize such systems. The classical PID and LQ correction methods are widely used. If the latter represent the advantage to be simple because they are linear, they reveal the drawback to require the presence of a linear model to synthesize. It also implies the complexity of the established laws of command because the latter must be widened on all the domain of flight of these quadcopter. Note that, if the classical design methods are widely used to control aeronautical systems, the Artificial Intelligence methods as genetic algorithms technique receives little attention. In this paper, we suggest comparing two PID design methods. Firstly, the parameters of the PID are calculated according to the reference model. In a second phase, these parameters are established using genetic algorithms. By reference model, we mean that the corrected system behaves according to a reference system, imposed by some specifications: settling time, zero overshoot etc. Inspired from the natural evolution of Darwin's theory advocating the survival of the best, John Holland developed this evolutionary algorithm. Genetic algorithm (GA) possesses three basic operators: selection, crossover and mutation. We start iterations with an initial population. Each member of this population is evaluated through a fitness function. Our purpose is to correct the behavior of the quadcopter around three axes (roll, pitch and yaw) with 3 PD controllers. For the altitude, we adopt a PID controller.

Keywords: quadcopter, genetic algorithm, PID, fitness, model, control, nonlinear system

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4797 Optimal Portfolio Selection under Treynor Ratio Using Genetic Algorithms

Authors: Imad Zeyad Ramadan

Abstract:

In this paper a genetic algorithm was developed to construct the optimal portfolio based on the Treynor method. The GA maximizes the Treynor ratio under budget constraint to select the best allocation of the budget for the companies in the portfolio. The results show that the GA was able to construct a conservative portfolio which includes companies from the three sectors. This indicates that the GA reduced the risk on the investor as it choose some companies with positive risks (goes with the market) and some with negative risks (goes against the market).

Keywords: oOptimization, genetic algorithm, portfolio selection, Treynor method

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4796 In vitro Determination of Carbonic Anhydrase Inhibition of the Flowers of Vanda Orchid, Vanda Tessellata Roxb. (1795) by Modified Colorimetric Maren T.H. (1960) Method

Authors: John Carlo Combista, Jimbert Tan

Abstract:

The orchid, Vanda tessellata was chosen by the researchers because of the presence of the constituents in the family Orchidaceae such as alkaloids, flavonoids and glycosides that might give an inhibition activity of the carbonic anhydrase enzyme. This study aimed to determine the in vitro inhibition of carbonic anhydrase of Vanda tessellata flower extract. With the use of modified colorimetric Maren T.H. (1960) method, the time in seconds each test solution changed its color after the rate of CO2 hydration were recorded. Two solvents were used: the semi-polar, 95% ethanol and the non-polar, dichloromethane solvents. The percent inhibition activity of carbonic anhydrase of the different concentrations of solvents ethanol (1%, 25% and 50%) and dichloromethane (1% and 10%) test solutions were determined. Results showed that the ethanol-based extract of Vanda tessellata in different concentrations showed an inhibitory effect while the dichloromethane-based extract of Vanda tessellata showed no inhibitory effect of carbonic anhydrase activity. For ethanol extract, the concentration with the highest activity was 50% followed by 25% which changed its color from red to yellow with an average time of 13.11 seconds and 11.57 seconds but 1% with an average time of 7.56 seconds did not exhibit an effect. The researchers recommend the isolation of the specific active constituents of Vanda tessellata that is responsible for the inhibitory effect of carbonic anhydrase enzyme. It is also recommended to utilize different blood types to observe different reactions to the inhibition of the carbonic anhydrase.

Keywords: carbonic anhydrase, inhibition, modified colorimetric Maren TH method, Vanda orchid

Procedia PDF Downloads 298
4795 Estimation of Seismic Deformation Demands of Tall Buildings with Symmetric Setbacks

Authors: Amir Alirezaei, Shahram Vahdani

Abstract:

This study estimates the seismic demands of tall buildings with central symmetric setbacks by using nonlinear time history analysis. Three setback structures, all 60-story high with setback in three levels, are used for evaluation. The effects of irregularities occurred by setback, are evaluated by determination of global-drift, story-displacement and story drift. Story-displacement is modified by roof displacement and first story displacement and story drift is modified by global drift. All results are calculated at the center of mass and in x and y direction. Also the absolute values of these quantities are determined. The results show that increasing of vertical irregularities increases the global drift of the structure and enlarges the deformations in the height of the structure. It is also observed that the effects of geometry irregularity in the seismic deformations of setback structures are higher than those of mass irregularity.

Keywords: deformation demand, drift, setback, tall building

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4794 Transesterification of Waste Cooking Oil for Biodiesel Production Using Modified Clinoptilolite Zeolite as a Heterogeneous Catalyst

Authors: D. Mowla, N. Rasti, P. Keshavarz

Abstract:

Reduction of fossil fuels sources, increasing of pollution gases emission, and global warming effects increase the demand of renewable fuels. One of the main candidates of alternative fuels is biodiesel. Biodiesel limits greenhouse gas effects due to the closed CO2 cycle. Biodiesel has more biodegradability, lower combustion emissions such as CO, SOx, HC, PM and lower toxicity than petro diesel. However, biodiesel has high production cost due to high price of plant oils as raw material. So, the utilization of waste cooking oils (WCOs) as feedstock, due to their low price and disposal problems reduce biodiesel production cost. In this study, production of biodiesel by transesterification of methanol and WCO using modified sodic potassic (SP) clinoptilolite zeolite and sodic potassic calcic (SPC) clinoptilolite zeolite as heterogeneous catalysts have been investigated. These natural clinoptilolite zeolites were modified by KOH solution to increase the site activity. The optimum biodiesel yields for SP clinoptilolite and SPC clinoptilolite were 95.8% and 94.8%, respectively. Produced biodiesel were analyzed and compared with petro diesel and ASTM limits. The properties of produced biodiesel confirm well with ASTM limits. The density, kinematic viscosity, cetane index, flash point, cloud point, and pour point of produced biodiesel were all higher than petro diesel but its acid value was lower than petro diesel. Finally, the reusability and regeneration of catalysts were investigated. The results indicated that the spent zeolites cannot be reused directly for the transesterification, but they can be regenerated easily and can obtain high activity.

Keywords: biodiesel, renewable fuel, transesterification, waste cooking oil

Procedia PDF Downloads 240
4793 Effect of Sodium Alginate-based Edible Coating with Natural Essential Oils and Modified Atmosphere Packaging on Quality of Fresh-cut Pineapple

Authors: Muhammad Rafi Ullah Khan, Yaodong Guo, Vanee Chonhenchob, Jinjin Pei, Chongxing Huang

Abstract:

The effect of sodium alginate (1%) based edible coating incorporated natural essential oils; thymol, carvone and carvacrol as antimicrobial agents at different concentrations (0.1, 0.5 and 1.0 %) on the quality changes of fresh-cut pineapple were investigated. Pineapple dipped in distilled water was served as control. After coating, fruit were sealed in a modified atmosphere package (MAP) using high permeable film; and stored at 5 °C. Gas composition in package headspace, color values (L*, a*, b*, C*), TSS, pH, ethanol, browning, and microbial decay were monitored during storage. Oxygen concentration continuously decreased while carbon dioxide concentration inside all packages continuously increased over time. Color parameters (L*, b*, c*) decreased and a* values increased during storage. All essential oils significantly (p ≤ 0.05) prevented microbial growth than control. A significantly higher (p ≤ 0.05) ethanol content was found in the control than in all other treatments. Visible microbial growth, high ethanol, and low color values limited the shelf life to 6 days in control as compared to 9 days in all other treatments. Among all essential oils, thymol at all concentrations maintained the overall quality of the pineapple and could potentially be used commercially in fresh fruit industries for longer storage.

Keywords: essential oils, antibrowning agents, antimicrobial agents, modified atmosphere packaging, microbial decay, pineapple

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4792 RA-Apriori: An Efficient and Faster MapReduce-Based Algorithm for Frequent Itemset Mining on Apache Flink

Authors: Sanjay Rathee, Arti Kashyap

Abstract:

Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

Procedia PDF Downloads 298
4791 Modelling Fluoride Pollution of Groundwater Using Artificial Neural Network in the Western Parts of Jharkhand

Authors: Neeta Kumari, Gopal Pathak

Abstract:

Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

Procedia PDF Downloads 551
4790 Biosensors for Parathion Based on Au-Pd Nanoparticles Modified Electrodes

Authors: Tian-Fang Kang, Chao-Nan Ge, Rui Li

Abstract:

An electrochemical biosensor for the determination of organophosphorus pesticides was developed based on electrochemical co-deposition of Au and Pd nanoparticles on glassy carbon electrode (GCE). Energy disperse spectroscopy (EDS) analysis was used for characterization of the surface structure. Scanning electron micrograph (SEM) demonstrates that the films are uniform and the nanoclusters are homogeneously distributed on the GCE surface. Acetylcholinesterase (AChE) was immobilized on the Au and Pd nanoparticle modified electrode (Au-Pd/GCE) by cross-linking with glutaraldehyde. The electrochemical behavior of thiocholine at the biosensor (AChE/Au-Pd/GCE) was studied. The biosensors exhibited substantial electrocatalytic effect on the oxidation of thiocholine. The peak current of linear scan voltammetry (LSV) of thiocholine at the biosensor is proportional to the concentration of acetylthiocholine chloride (ATCl) over the range of 2.5 × 10-6 to 2.5 × 10-4 M in 0.1 M phosphate buffer solution (pH 7.0). The percent inhibition of acetylcholinesterase was proportional to the logarithm of parathion concentration in the range of 4.0 × 10-9 to 1.0 × 10-6 M. The detection limit of parathion was 2.6 × 10-9 M. The proposed method exhibited high sensitivity and good reproducibility.

Keywords: acetylcholinesterase, Au-Pd nanoparticles, electrochemical biosensors, parathion

Procedia PDF Downloads 407
4789 Probabilistic Gathering of Agents with Simple Sensors: Distributed Algorithm for Aggregation of Robots Equipped with Binary On-Board Detectors

Authors: Ariel Barel, Rotem Manor, Alfred M. Bruckstein

Abstract:

We present a probabilistic gathering algorithm for agents that can only detect the presence of other agents in front of or behind them. The agents act in the plane and are identical and indistinguishable, oblivious, and lack any means of direct communication. They do not have a common frame of reference in the plane and choose their orientation (direction of possible motion) at random. The analysis of the gathering process assumes that the agents act synchronously in selecting random orientations that remain fixed during each unit time-interval. Two algorithms are discussed. The first one assumes discrete jumps based on the sensing results given the randomly selected motion direction, and in this case, extensive experimental results exhibit probabilistic clustering into a circular region with radius equal to the step-size in time proportional to the number of agents. The second algorithm assumes agents with continuous sensing and motion, and in this case, we can prove gathering into a very small circular region in finite expected time.

Keywords: control, decentralized, gathering, multi-agent, simple sensors

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4788 Urea Amperometric Biosensor Based on Entrapment Immobilization of Urease onto a Nanostructured Polypyrrol and Multi-Walled Carbon Nanotube

Authors: Hamide Amani, Afshin FarahBakhsh, Iman Farahbakhsh

Abstract:

In this paper, an amprometric biosensor based on surface modified polypyrrole (PPy) has been developed for the quantitative estimation of urea in aqueous solutions. The incorporation of urease (Urs) into a bipolymeric substrate consisting of PPy was performed by entrapment to the polymeric matrix, PPy acts as amperometric transducer in these biosensors. To increase the membrane conductivity, multi-walled carbon nanotubes (MWCNT) were added to the PPy solution. The entrapped MWCNT in PPy film and the bipolymer layers were prepared for construction of Pt/PPy/MWCNT/Urs. Two different configurations of working electrodes were evaluated to investigate the potential use of the modified membranes in biosensors. The evaluation of two different configurations of working electrodes suggested that the second configuration, which was composed of an electrode-mediator-(pyrrole and multi-walled carbon nanotube) structure and enzyme, is the best candidate for biosensor applications.

Keywords: urea biosensor, polypyrrole, multi-walled carbon nanotube, urease

Procedia PDF Downloads 331
4787 Entropy Production in Mixed Convection in a Horizontal Porous Channel Using Darcy-Brinkman Formulation

Authors: Amel Tayari, Atef Eljerry, Mourad Magherbi

Abstract:

The paper reports a numerical investigation of the entropy generation analysis due to mixed convection in laminar flow through a channel filled with porous media. The second law of thermodynamics is applied to investigate the entropy generation rate. The Darcy-Brinkman Model is employed. The entropy generation due to heat transfer and friction dissipations has been determined in mixed convection by solving numerically the continuity, momentum and energy equations, using a control volume finite element method. The effects of Darcy number, modified Brinkman number and the Rayleigh number on averaged entropy generation and averaged Nusselt number are investigated. The Rayleigh number varied between 103 ≤ Ra ≤ 105 and the modified Brinkman number ranges between 10-5 ≤ Br≤ 10-1 with fixed values of porosity and Reynolds number at 0.5 and 10 respectively. The Darcy number varied between 10-6 ≤ Da ≤10.

Keywords: entropy generation, porous media, heat transfer, mixed convection, numerical methods, darcy, brinkman

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4786 Development of a Sensitive Electrochemical Sensor Based on Carbon Dots and Graphitic Carbon Nitride for the Detection of 2-Chlorophenol and Arsenic

Authors: Theo H. G. Moundzounga

Abstract:

Arsenic and 2-chlorophenol are priority pollutants that pose serious health threats to humans and ecology. An electrochemical sensor, based on graphitic carbon nitride (g-C₃N₄) and carbon dots (CDs), was fabricated and used for the determination of arsenic and 2-chlorophenol. The g-C₃N₄/CDs nanocomposite was prepared via microwave irradiation heating method and was dropped-dried on the surface of the glassy carbon electrode (GCE). Transmission electron microscopy (TEM), X-ray diffraction (XRD), photoluminescence (PL), Fourier transform infrared spectroscopy (FTIR), UV-Vis diffuse reflectance spectroscopy (UV-Vis DRS) were used for the characterization of structure and morphology of the nanocomposite. Electrochemical characterization was done by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The electrochemical behaviors of arsenic and 2-chlorophenol on different electrodes (GCE, CDs/GCE, and g-C₃N₄/CDs/GCE) was investigated by differential pulse voltammetry (DPV). The results demonstrated that the g-C₃N₄/CDs/GCE significantly enhanced the oxidation peak current of both analytes. The analytes detection sensitivity was greatly improved, suggesting that this new modified electrode has great potential in the determination of trace level of arsenic and 2-chlorophenol. Experimental conditions which affect the electrochemical response of arsenic and 2-chlorophenol were studied, the oxidation peak currents displayed a good linear relationship to concentration for 2-chlorophenol (R²=0.948, n=5) and arsenic (R²=0.9524, n=5), with a linear range from 0.5 to 2.5μM for 2-CP and arsenic and a detection limit of 2.15μM and 0.39μM respectively. The modified electrode was used to determine arsenic and 2-chlorophenol in spiked tap and effluent water samples by the standard addition method, and the results were satisfying. According to the measurement, the new modified electrode is a good alternative as chemical sensor for determination of other phenols.

Keywords: electrochemistry, electrode, limit of detection, sensor

Procedia PDF Downloads 145
4785 The Effect of Hydroxyl Ethyl Cellulose (HEC) and Hydrophobically-Modified Alkali Soluble Emulsions (HASE) on the Properties and Quality of Water Based Paints

Authors: Haleden Chiririwa, Sandile S. Gwebu

Abstract:

The coatings industry is a million dollar business, and it is easy and inexpensive to set-up but it is growing very slowly in developing countries, and this study developed a paint formulation which gives better quality and good application properties. The effect of rheology modifiers, i.e. non-ionic polymers hydrophobically-modified ethoxylated urethanes (HEUR), anionic polymers hydrophobically-modified alkali soluble emulsions (HASE) and hydroxyl ethyl cellulose (HEC) on the quality and properties of water-based paints have been investigated. HEC provides the in-can viscosity and increases open working time while HASE improves application properties like spatter resistance and brush loading and HEUR provides excellent scrub resistance. Four paint recipes were prepared using four different thickeners HEC, HASE (carbopol) and Cellulose nitrate. The fourth formulation was thickened with a combination of HASE and HEC, this aimed at improving quality and at the same time reducing cost. The four samples were tested for quality tests such viscosity, sag resistance, volatile matter, tinter effect, drying times, hiding power, scrub resistance and stability on storage. Environmental factors were incorporated in the attempt to formulate an economic and green product. Hydroxyl ethyl cellulose and cellulose nitrate gave high quality and good properties of the paint. HEC and Cellulose nitrate showed stability on storage whereas carbopol thickener was very unstable.

Keywords: properties, thickeners, rheology modifiers, water based paints

Procedia PDF Downloads 268