Search results for: microcosm experiments

Authors: Mohamed Zakaulla, A. R. Anwar Khan

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Al6061 alloy base matrix, reinforced with particles of silicon carbide (10 wt %) and Graphite powder (1wt%), known as hybrid composites have been fabricated by liquid metallurgy route (stir casting technique) and optimized at different parameters like applied load, sliding speed and sliding distance by taguchi method. A plan of experiment generated through taguchi technique was used to perform experiments based on L27 orthogonal array. The developed ANOVA and regression equations are used to find the optimum coefficient of friction and wear under the influence of applied load, sliding speed and sliding distance. On the basis of “smaller the best” the dry sliding wear resistance was analysed and finally confirmation tests were carried out to verify the experimental results.

Keywords: analysis of variance, dry sliding wear, hybrid composite, orthogonal array, Taguchi technique

Procedia PDF Downloads 454

Authors: Zahra Khalid, Gul Muhammad Khan, Arbab Masood Ahmad

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Cartesian Genetic Programming (CGP) is explored to design an optimal circuit capable of early stage breast cancer detection. CGP is used to evolve simple multiplexer circuits for detection of malignancy in the Fine Needle Aspiration (FNA) samples of breast. The data set used is extracted from Wisconsins Breast Cancer Database (WBCD). A range of experiments were performed, each with different set of network parameters. The best evolved network detected malignancy with an accuracy of 99.14%, which is higher than that produced with most of the contemporary non-linear techniques that are computational expensive than the proposed system. The evolved network comprises of simple multiplexers and can be implemented easily in hardware without any further complications or inaccuracy, being the digital circuit.

Keywords: breast cancer detection, cartesian genetic programming, evolvable hardware, fine needle aspiration

Procedia PDF Downloads 206

Authors: A. Sadeghi, M. Sedghi, M. R. Emami Azadi, R. Gharraei Khosroshahi

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Flags are objects with very low bending stiffness and under wind forces start to vibrate and finally to flutter. Even in lower velocities of wind their flutter can be seen. In this research physical property of fabric is determined by performing tensile tests. Then with performing laboratory experiments in wind tunnel, determination of initial flapping speed and also study of displacement amplitude at leech and calculation of their frequency would be targeted. Laboratory tests are performed in a wind tunnel and with different velocities of wind flow for specimens with different dimensions. The results show that extension of specimens' width increase flutter initiation velocity and increase of specimen length decreases it. Also by increasing wind velocity displacement amplitude at leech of specimens are decreased. This displacement has a straight relation with specimens' length and width.

Keywords: flag, flutter, wind velocity, flutter amplitudes, wind tunnel

Procedia PDF Downloads 424

Authors: Isik Cetintav, Cenk Misirli, Yilmaz Can, Damla Gunel

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This work investigates experimental and numerical analysis of open die forging of multimetallic materials. Multimetallic material production has recently become an interesting research field. The mechanical properties of the materials to be used for the formation of multimetallic materials and the mechanical properties of the multimetallic materials produced will be compared and the material flows of the use of different lubricants will be examined. Furthermore, in this work, the mechanical properties of multimetallic metallic materials produced using different materials will be examined by using different lubricants. The advantages and disadvantages of different lubricants will be approached with the bi-metallic material to be produced. Cylindrical specimens consisting of two different materials were used in the experiments. Specimens were prepared as aluminum sleeve and copper core and upset at different reduction. This metal combination present a material model of which chemical composition is different. ABAQUS software was used for the simulations. Simulation and experimental results have also shown reasonable agreement.

Keywords: multimetallic, forging, experimental, numerical

Procedia PDF Downloads 269

Authors: M. Capocelli, A. Caputo, M. De Falco, D. Mazzei, V. Piemonte

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This paper presents the experimental results and the related modeling of a thermal energy storage (TES) facility, ideated and realized by ENEA and realizing the thermocline with an innovative geometry. Firstly, the thermal energy exchange model of an equivalent shell & tube heat exchanger is described and tested to reproduce the performance of the spiral exchanger installed in the TES. Through the regression of the experimental data, a first-order thermocline model was also validated to provide an analytical function of the thermocline, useful for the performance evaluation and the comparison with other systems and implementation in simulations of integrated systems (e.g. power plants). The experimental data obtained from the plant start-up and the short-cut modeling of the system can be useful for the process analysis, for the scale-up of the thermal storage system and to investigate the feasibility of its implementation in actual case-studies.

Keywords: CSP plants, thermal energy storage, thermocline, mathematical modelling, experimental data

Procedia PDF Downloads 319

Authors: Austin Ikechukwu Gbasouzor, Sam Nna Omenyi, Sabuj Malli

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This study is an extension of the previous work done with ARS-680 Environmental Chamber. Drying is a complex operation that demands much energy and time. Drying is essentially important for preservation of ginger rhizome. Drying of ginger was modeled, and then the effective diffusion coefficient and activation energy where determined. For this purpose, the experiments were done at six levels of varied temperature ranging from (10, 20, 30, 40, 50, 60°C). The average effective diffusion coefficient for their studies samples for temperature range of 40°C to 70°C was 4.48 x10-10m²/s, 4.96 x10-10m²/s, and 5.31 x10-10m²/s for 0.8, 1.5 and 3m/s drying air velocity respectively. These values closely agreed with the values of effective diffusion coefficients obtained in these studies for the variously treated ginger rhizomes and test conducted.

Keywords: activation energy, diffusion coefficients, drying model, drying time, ginger rhizomes, moisture ratio, thin layer

Procedia PDF Downloads 154

Authors: Rajaramamohanarao Chennu, S. Sudhakara Reddy, Gurudev T, Maroti

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With the invent of recent available technology and cost optimization, the switchgear assemblies are becoming more compact and designed to operate at critical levels of thermal and dielectric stress. At the same time, the switchgear assemblies shall be designed for protection of persons, met in the event of internal arc for specified installation conditions, according to the latest available national/international standards. These standards are revising regularly for better product design and personal safety. The switchgear assemblies design shall be modified in accordance with the change in requirements in the latest edition of the standards. This paper presents the signifying changes brought in the latest edition of 62271-200:2021 and effect of these changes and the necessitated design improvements for meeting internal arc test requirements is presented by carrying out the internal arc testing experiments on the switchgear assemblies at High Power Laboratory, Central Power Research Institute, Bangalore, India.

Keywords: internal arc, switchgear assembly, high speed videography, IEC 62271-200

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Authors: Song Zhiyong, Zhao Bo, Du Li, Wang Wei

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Aircraft structures generally have complex surface. Because of constantly switching postures of motion axis, five-axis CNC machine’s composite stiffness changes during CNC machining. It gives rise to different amplitude of vibration of processing system, which further leads to the different effects on surface waviness. In order to provide a solution for this problem, we take the “S” shape test specimen’s CNC machining for the object, through calculate the five axis CNC machine’s composite stiffness and establish vibration model, we analysis of the influence mechanism between vibration amplitude and surface waviness. Through carry out the surface quality measurement experiments, verify the validity and accuracy of the theoretical analysis. This paper’s research results provide a theoretical basis for surface waviness control.

Keywords: five axis CNC machine, “S” shape test specimen, composite stiffness, surface waviness

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Authors: Somar Boubou, Tatsuo Narikiyo, Michihiro Kawanishi

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In this work, we address the problem of 3D object recognition with depth sensors such as Kinect or Structure sensor. Compared with traditional approaches based on local descriptors, which depends on local information around the object key points, we propose a global features based descriptor. Proposed descriptor, which we name as Differential Histogram of Normal Vectors (DHONV), is designed particularly to capture the surface geometric characteristics of the 3D objects represented by depth images. We describe the 3D surface of an object in each frame using a 2D spatial histogram capturing the normalized distribution of differential angles of the surface normal vectors. The object recognition experiments on the benchmark RGB-D object dataset and a self-collected dataset show that our proposed descriptor outperforms two others descriptors based on spin-images and histogram of normal vectors with linear-SVM classifier.

Keywords: vision in control, robotics, histogram, differential histogram of normal vectors

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Authors: Pavel Boška, Jan Bomba, Tomáš Beránek, Jiří Procházka

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When using wood products bonded by polyvinyl acetate, glues such as windows are the most limiting element of degradation of the glued joint due to weather changes. In addition to moisture and high temperatures, the joint may damage the low temperature below freezing point, where dimensional changes in the material and distortion of the adhesive film occur. During the experiments, the joints were exposed to several degrees of sub-zero temperatures from 0 °C to -40 °C and then to compare how the decreasing temperature affects the strength of the joint. The experiment was performed on wood beech samples (Fagus sylvatica), bonded with PVAc with D3 resistance and the shear strength of bond was measured. The glued and treated samples were tested on a laboratory testing machine, recording the strength of the joint. The statistical results have given us information that the strength of the joint gradually decreases with decreasing temperature, but a noticeable and statistically significant change is achieved only at very low temperatures.

Keywords: adhesives, bond strength, low temperatures, polyvinyl acetate

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Authors: Juan Ignacio Arango, Andres Diaz, Giacomo Barbieri

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In soilless culture, the definition of efficient fertigation strategies is fundamental for the growth of crops. Flexible test-benches able to independently manage groups of crops are key for investigating efficient fertigation practices through experimentation. These test-benches must be able to provide nutrient solution (NS) in a precise, uniform and repeatable way in order to effectively implement and compare different fertigation strategies. This article describes a distribution module for investigating fertigation practices able to control the fertigation dose and frequency. The proposed solution is characterized in terms of precision, uniformity and repeatability since these parameters are fundamental in the implementation of effective experiments for the investigation of fertigation practices. After a calibration process, the implemented system reaches a precision of 1mL, a uniformity of 98.5% at a total cost of 735USD.

Keywords: recision horticulture, test-bench, fertigation strategy, automation, flexibility

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Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

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Dissolved Gas Analysis (DGA) has been widely used for fault diagnosis in a transformer. Artificial neural networks (ANN) have high accuracy but are regarded as black boxes that are difficult to interpret. For many problems it is desired to extract knowledge from trained neural networks (NN) so that the user can gain a better understanding of the solution arrived by the NN. This paper applies a pedagogical approach for rule extraction from function approximating neural networks (REFANN) with application to incipient fault diagnosis using the concentrations of the dissolved gases within the transformer oil, as the input to the NN. The input space is split into subregions and for each subregion there is a linear equation that is used to predict the type of fault developing within a transformer. The experiments on real data indicate that the approach used can extract simple and useful rules and give fault predictions that match the actual fault and are at times also better than those predicted by the IEC method.

Keywords: artificial neural networks, dissolved gas analysis, rules extraction, transformer

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Authors: S. Sulaiman, M. A. Razak, M. R. Ibrahim, A. A. Khan

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An experimental work on the effect of different current and pulse duration on performance of EDM process of Allegheny Ludlum D2 Tool Steel (UNS T30402). The effect of varying the machining parameters on the machining responses such as material removal rate (MRR), electrode wear rate (EWR), and surface roughness (Ra) have been investigated. In this study, triangular shape and circular shape of copper was used as an electrode with surface area of 100 mm². The experiments were repeated for three different values of pulse duration (100 µs, 200 µs and 400 µs) with combination of three different values of discharge current (12 A, 16 A and 24 A). It was found that the pulse duration and current have significant effect on MRR, EWR and Ra. An increase in the pulse durations causes an increase in the MRR and Ra, but a decrease in the EWR. Meanwhile, the effect of currents on EDM performance shows that the increasing currents lead to an increase in the MRR, EWR and Ra.

Keywords: allegheny ludlum D2 tool steel, current, EDM, surface roughness, pulse duration

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Authors: Salima Behdenna, Fatiha Barigou, Ghalem Belalem

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Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic aspect-based sentiment analysis approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.

Keywords: sentiment analysis, opinion mining, Arabic, aspect level, opinion, polarity

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Authors: Kevin Fernagut, Olivier Flauzac, Erick M. G. Robledo, Florent Nolot

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The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-Based Virtual Machine (KVM), Linux Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: containerization, containers, cybersecurity, cyberattacks, isolation, performance, virtualization, virtual machines

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Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh

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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.

Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data

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Authors: Murat Sarıkaya, Abdulkadir Güllü

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Haynes 25 alloy (also known as L-605 alloy) is cobalt based super alloy which has widely applications such as aerospace industry, turbine and furnace parts, power generators and heat exchangers and petroleum refining components due to its excellent characteristics. However, the workability of this alloy is more difficult compared to normal steels or even stainless. In present work, an experimental investigation was performed under cryogenic cooling to determine cutting tool wear patterns and obtain optimal cutting parameters in turning of cobalt based superalloy Haynes 25. In experiments, uncoated carbide tool was used and cutting speed (V) and feed rate (f) were considered as test parameters. Tool wear (VBmax) were measured for process performance indicators. Analysis of variance (ANOVA) was performed to determine the importance of machining parameters.

Keywords: cryogenic machining, difficult-to-cut alloy, tool wear, turning

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Authors: Ashok Kumar, Shiv Brat Singh, Kalyan Kumar Ray

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There is growing awareness to design steels against fatigue damage Ferrite martensite dual-phase steels are known to exhibit favourable mechanical properties like good strength, ductility, toughness, continuous yielding, and high work hardening rate. However, dual-phase steels containing bainite as second phase are potential alternatives for ferrite martensite steels for certain applications where good fatigue property is required. Fatigue properties of dual phase steels are popularly assessed by the nature of variation of crack growth rate (da/dN) with stress intensity factor range (∆K), and the magnitude of fatigue threshold (∆Kth) for long cracks. There exists an increased emphasis to understand not only the long crack fatigue behavior but also short crack growth behavior of ferrite bainite dual phase steels. The major objective of this report is to examine the influence of microstructures on the short and long crack growth behavior of a series of developed dual-phase steels with varying amounts of bainite and. Three low carbon steels containing Nb, Cr and Mo as microalloying elements steels were selected for making ferrite-bainite dual-phase microstructures by suitable heat treatments. The heat treatment consisted of austenitizing the steel at 1100°C for 20 min, cooling at different rates in air prior to soaking these in a salt bath at 500°C for one hour, and finally quenching in water. Tensile tests were carried out on 25 mm gauge length specimens with 5 mm diameter using nominal strain rate 0.6x10⁻³ s⁻¹ at room temperature. Fatigue crack growth studies were made on a recently developed specimen configuration using a rotating bending machine. The crack growth was monitored by interrupting the test and observing the specimens under an optical microscope connected to an Image analyzer. The estimated crack lengths (a) at varying number of cycles (N) in different fatigue experiments were analyzed to obtain log da/dN vs. log °∆K curves for determining ∆Kthsc. The microstructural features of these steels have been characterized and their influence on the near threshold crack growth has been examined. This investigation, in brief, involves (i) the estimation of ∆Kthsc and (ii) the examination of the influence of microstructure on short and long crack fatigue threshold. The maximum fatigue threshold values obtained from short crack growth experiments on various specimens of dual-phase steels containing different amounts of bainite are found to increase with increasing bainite content in all the investigated steels. The variations of fatigue behavior of the selected steel samples have been explained with the consideration of varying amounts of the constituent phases and their interactions with the generated microstructures during cyclic loading. Quantitative estimation of the different types of fatigue crack paths indicates that the propensity of a crack to pass through the interfaces depends on the relative amount of the microstructural constituents. The fatigue crack path is found to be predominantly intra-granular except for the ones containing > 70% bainite in which it is predominantly inter-granular.

Keywords: bainite, dual phase steel, fatigue crack growth rate, long crack fatigue threshold, short crack fatigue threshold

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Authors: Reza Rezaeipour Honarmandzad

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In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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Authors: Asad Naeem, Jinkoo Kim

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This research proposes a self-centering passive damping system consisting of a spring viscous damper linked with a preloaded tendon. The seismic performance of the spring viscous damper is evaluated by pseudo-dynamic tests, and the results are used for the formulation of an analytical model of the damper in the structural analysis program. The shaking table tests of a two-story steel frame installed with the proposed damping system are carried out using five different earthquake records. The results from the shaking table tests are verified by numerical simulation of the retrofitted structure. The results obtained from experiments and numerical simulations demonstrate that the proposed damping system with self-centering capability is effective in reducing earthquake-induced displacement and member forces.

Keywords: seismic retrofit, spring viscous damper, shaking table test, earthquake resistant structures

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Authors: G. Carrero, C. Contreras, M. J. Hendzel

Abstract:

Linker histones or histones H1 are highly mobile nuclear proteins that regulate the organization of chromatin and limit DNA accessibility by binding to the chromatin structure (DNA and associated proteins). It is known that this binding process is driven by both slow (strong binding) and rapid (weak binding) interactions. However, the exact binding mechanism has not been fully described. Moreover, the existing models only account for one type of bound population that does not distinguish explicitly between the weakly and strongly bound proteins. Thus, we propose different systems of reaction-diffusion equations to describe explicitly the rapid and slow interactions during a FRAP (Fluorescence Recovery After Photobleaching) experiment. We perform a model comparison analysis to characterize the binding mechanism of histone H1 and provide new meaningful biophysical information on the kinetics of histone H1.

Keywords: FRAP (Fluorescence Recovery After Photobleaching), histone H1, histone H1 binding kinetics, linker histone, reaction-diffusion equation

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Dinara F. Gaynutdinova, Vladimir Ya Modorsky, Nikolay A. Shevelev

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The problem under research is that of unpredictable modes occurring in two-stage centrifugal hydraulic pump as a result of hydraulic processes caused by vibrations of structural components. Numerical, analytical and experimental approaches are considered. A hypothesis was developed that the problem of unpredictable pressure decrease at the second stage of centrifugal pumps is caused by cavitation effects occurring upon vibration. The problem has been studied experimentally and theoretically as of today. The theoretical study was conducted numerically and analytically. Hydroelastic processes in dynamic “liquid – deformed structure” system were numerically modelled and analysed. Using ANSYS CFX program engineering analysis complex and computing capacity of a supercomputer the cavitation parameters were established to depend on vibration parameters. An influence domain of amplitudes and vibration frequencies on concentration of cavitation bubbles was formulated. The obtained numerical solution was verified using CFM program package developed in PNRPU. The package is based on a differential equation system in hyperbolic and elliptic partial derivatives. The system is solved by using one of finite-difference method options – the particle-in-cell method. The method defines the problem solution algorithm. The obtained numerical solution was verified analytically by model problem calculations with the use of known analytical solutions of in-pipe piston movement and cantilever rod end face impact. An infrastructure consisting of an experimental fast hydro-dynamic processes research installation and a supercomputer connected by a high-speed network, was created to verify the obtained numerical solutions. Physical experiments included measurement, record, processing and analysis of data for fast processes research by using National Instrument signals measurement system and Lab View software. The model chamber end face oscillated during physical experiments and, thus, loaded the hydraulic volume. The loading frequency varied from 0 to 5 kHz. The length of the operating chamber varied from 0.4 to 1.0 m. Additional loads weighed from 2 to 10 kg. The liquid column varied from 0.4 to 1 m high. Liquid pressure history was registered. The experiment showed dependence of forced system oscillation amplitude on loading frequency at various values: operating chamber geometrical dimensions, liquid column height and structure weight. Maximum pressure oscillation (in the basic variant) amplitudes were discovered at loading frequencies of approximately 1,5 kHz. These results match the analytical and numerical solutions in ANSYS and CFM.

Keywords: computing experiment, hydroelasticity, physical experiment, vibration

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Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris

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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.

Keywords: cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization

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Authors: Ali Nourollah, Mohsen Movahedinejad

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In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The merge algorithm has the time complexity of O ((r+s) *l) where r and s are the size of merging polygons and l shows the number of intersecting edges removed from the polygonal chain. It will be shown that 1 < l < r+s. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

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Authors: Syeda Azeem Unnisa

Abstract:

The present study was undertaken at Jawaharnagar Solid Waste Municipal Dumpsite, Greater Hyderabad Municipal Corporation, Telangana State, India in 2017 which generates 90,000 litres of leachate per day. The main objective of the leachate treatment was to remove organic compounds like color, suspended solids, ammonia and COD by coagulation-flocculation using polyaluminum chloride (PAC) as coagulant which has higher coagulant efficiency and relative low cost compared to the conventional coagulants. Jar test apparatus was used to conduct experiments for pH 7, rapid mixing speed 150 rpm for 3 minute, slow mixing speed 30 rpm for 20 minute and the settling time of 30 minute for different dosage of PAC (0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5 and 5.0 g/L). The highest percentage of removal of suspended solids, color, COD and ammonical nitrogen are 97%, 96%, 60% and 37% with PAC optimum dose of 2.0 g/l. The results indicate that the PAC was effective in leachate treatment which is very much suitable for high toxicity of waste and economically feasible for Indian conditions. The treated water can be utilized for other purpose apart from drinking.

Keywords: coagulant, leachate, polyaluminium chloride, treatment

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Authors: Md Abdullah Al Faruque

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A very large percentage of bridge failures are attributed to scouring around bridge piers and this directly influences public safety. Experiments are carried out in a 12-m long rectangular open channel flume made of transparent tempered glass. A 300 mm thick bed made up of sand particles is leveled horizontally to create the test bed and a 50 mm hollow plastic cylinder is used as a model bridge pier. Tests are carried out with varying flow depths and velocities. Data points of various scour parameters such as scour depth, width, and length are collected based on different flow conditions and visual observations of changes in the stream bed downstream the bridge pier are also made as the scour progresses. Result shows that all three major flow characteristics (flow depth, Froude number and densimetric Froude number) have one way or other affect the scour profile.

Keywords: bridge pier scour, densimetric Froude number, flow depth, Froude number, sand

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Authors: Minh Quang Le, Dane Taylor

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Convection is a well-studied topic in fluid dynamics, yet it is less understood in the context of networks flows. Here, we incorporate techniques from topological data analysis (namely, persistent homology) to automate the detection and characterization of convective/cyclic/chiral flows over networks, particularly those that arise for irreversible Markov chains (MCs). As two applications, we study convection cycles arising under the PageRank algorithm, and we investigate chiral edges flows for a stochastic model of a bi-monomer's configuration dynamics. Our experiments highlight how system parameters---e.g., the teleportation rate for PageRank and the transition rates of external and internal state changes for a monomer---can act as homology regularizers of convection, which we summarize with persistence barcodes and homological bifurcation diagrams. Our approach establishes a new connection between the study of convection cycles and homology, the branch of mathematics that formally studies cycles, which has diverse potential applications throughout the sciences and engineering.

Keywords: homology, persistent homolgy, markov chains, convection cycles, filtration

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Authors: Mohammed Makki, Milad Showkatbakhsh, Aiman Tabony

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Computational applications of natural evolutionary processes as problem-solving tools have been well established since the mid-20th century. However, their application within architecture and design has only gained ground in recent years, with an increasing number of academics and professionals in the field electing to utilize evolutionary computation to address problems comprised from multiple conflicting objectives with no clear optimal solution. Recent advances in computer science and its consequent constructive influence on the architectural discourse has led to the emergence of multiple algorithmic processes capable of simulating the evolutionary process in nature within an efficient timescale. Many of the developed processes of generating a population of candidate solutions to a design problem through an evolutionary based stochastic search process are often driven through the application of both environmental and architectural parameters. These methods allow for conflicting objectives to be simultaneously, independently, and objectively optimized. This is an essential approach in design problems with a final product that must address the demand of a multitude of individuals with various requirements. However, one of the main challenges encountered through the application of an evolutionary process as a design tool is the ability for the simulation to maintain variation amongst design solutions in the population while simultaneously increasing in fitness. This is most commonly known as the ‘golden rule’ of balancing exploration and exploitation over time; the difficulty of achieving this balance in the simulation is due to the tendency of either variation or optimization being favored as the simulation progresses. In such cases, the generated population of candidate solutions has either optimized very early in the simulation, or has continued to maintain high levels of variation to which an optimal set could not be discerned; thus, providing the user with a solution set that has not evolved efficiently to the objectives outlined in the problem at hand. As such, the experiments presented in this paper seek to achieve the ‘golden rule’ by incorporating a mathematical fitness criterion for the development of an urban tissue comprised from the superblock as its primary architectural element. The mathematical value investigated in the experiments is the standard deviation factor. Traditionally, the standard deviation factor has been used as an analytical value rather than a generative one, conventionally used to measure the distribution of variation within a population by calculating the degree by which the majority of the population deviates from the mean. A higher standard deviation value delineates a higher number of the population is clustered around the mean and thus limited variation within the population, while a lower standard deviation value is due to greater variation within the population and a lack of convergence towards an optimal solution. The results presented will aim to clarify the extent to which the utilization of the standard deviation factor as a fitness criterion can be advantageous to generating fitter individuals in a more efficient timeframe when compared to conventional simulations that only incorporate architectural and environmental parameters.

Keywords: architecture, computation, evolution, standard deviation, urban

Procedia PDF Downloads 124