Search results for: robotic experiments

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

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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

Procedia PDF Downloads 441

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

Procedia PDF Downloads 163

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

Procedia PDF Downloads 244

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

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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

Procedia PDF Downloads 206

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: Efrain Rodriguez, Cristhian Riano, Alberto Alvares

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In recent years, robots manipulators with parallel architectures are used in additive manufacturing processes – 3D printing. These robots have advantages such as speed and lightness that make them suitable to help with the efficiency and productivity of these processes. Consequently, the interest for the development of parallel robots for additive manufacturing applications has increased. This article deals with the conceptual design and dimensional synthesis of the linear delta robot for additive manufacturing. Firstly, a methodology based on structured processes for the development of products through the phases of informational design, conceptual design and detailed design is adopted: a) In the informational design phase the Mudge diagram and the QFD matrix are used to aid a set of technical requirements, to define the form, functions and features of the robot. b) In the conceptual design phase, the functional modeling of the system through of an IDEF0 diagram is performed, and the solution principles for the requirements are formulated using a morphological matrix. This phase includes the description of the mechanical, electro-electronic and computational subsystems that constitute the general architecture of the robot. c) In the detailed design phase, a digital model of the robot is drawn on CAD software. A list of commercial and manufactured parts is detailed. Tolerances and adjustments are defined for some parts of the robot structure. The necessary manufacturing processes and tools are also listed, including: milling, turning and 3D printing. Secondly, a dimensional synthesis method applied on design of the linear delta robot is presented. One of the most important key factors in the design of a parallel robot is the useful workspace, which strongly depends on the joint space, the dimensions of the mechanism bodies and the possible interferences between these bodies. The objective function is based on the verification of the kinematic model for a prescribed cylindrical workspace, considering geometric constraints that possibly lead to singularities of the mechanism. The aim is to determine the minimum dimensional parameters of the mechanism bodies for the proposed workspace. A method based on genetic algorithms was used to solve this problem. The method uses a cloud of points with the cylindrical shape of the workspace and checks the kinematic model for each of the points within the cloud. The evolution of the population (point cloud) provides the optimal parameters for the design of the delta robot. The development process of the linear delta robot with optimal dimensions for additive manufacture is presented. The dimensional synthesis enabled to design the mechanism of the delta robot in function of the prescribed workspace. Finally, the implementation of the robotic platform developed based on a linear delta robot in an additive manufacturing application using the Fused Deposition Modeling (FDM) technique is presented.

Keywords: additive manufacturing, delta parallel robot, dimensional synthesis, genetic algorithms

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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

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Authors: Kazumasa Kawasaki, Katsuya Fukazawa

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Nickel-based superalloys are an important class of engineering material within the aerospace and power generation, due to their excellent combination of corrosion resistance and mechanical properties, including high-temperature applications Inconel 625 is one of such superalloys and difficult-to-machine material. In cutting of Inconel 625 superalloy with a ball end mill, the problem of adhesive wear often occurs. However, the proper cutting conditions are not known so much because of lack of study examples. In this study, the experiments using ball end mills made of carbide tools were tried to find the best cutting conditions out following qualifications. Using Inconel 625 superalloy as a work material, three kinds of experiment, with the revolution speed of 5000 rpm, 8000 rpm, and 10000 rpm, were performed under dry cutting conditions in feed speed per tooth of 0.045 mm/ tooth, depth of cut of 0.1 mm. As a result, in the case of 8000 rpm, it was successful to cut longest with the least wear.

Keywords: Inconel 625, ball end mill, carbide tool, high speed cutting, tool wear

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Authors: Xincheng Jiang, Yanyan An, Yaoyao Huang, Wei Ding, Manli Sun, Hong Li, Huaili Zheng

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The residual antibiotics in the environment will pose a threat to the environment and human health. Thus, efficient removal and rapid detection of norfloxacin (NOR) in wastewater is very important. The main sources of NOR pollution are the agricultural, pharmaceutical industry and hospital wastewater. The total consumption of NOR in China can reach 5440 tons per year. It is found that neither animals nor humans can totally absorb and metabolize NOR, resulting in the excretion of NOR into the environment. Therefore, residual NOR has been detected in water bodies. The hazards of NOR in wastewater lie in three aspects: (1) the removal capacity of the wastewater treatment plant for NOR is limited (it is reported that the average removal efficiency of NOR in the wastewater treatment plant is only 68%); (2) NOR entering the environment will lead to the emergence of drug-resistant strains; (3) NOR is toxic to many aquatic species. At present, the removal and detection technologies of NOR are applied separately, which leads to a cumbersome operation process. The development of simultaneous adsorption-flocculation removal and FTIR detection of pollutants has three advantages: (1) Adsorption-flocculation technology promotes the detection technology (the enrichment effect on the material surface improves the detection ability); (2) The integration of adsorption-flocculation technology and detection technology reduces the material cost and makes the operation easier; (3) FTIR detection technology endows the water treatment agent with the ability of molecular recognition and semi-quantitative detection for pollutants. Thus, it is of great significance to develop a smart water treatment material with high removal capacity and detection ability for pollutants. This study explored the feasibility of combining NOR removal method with the semi-quantitative detection method. A magnetic Cu-Ni-S/Ni foam was synthesized by in-situ loading Cu-Ni-S nanostructures on the surface of Ni foam. The novelty of this material is the combination of adsorption-flocculation technology and semi-quantitative detection technology. Batch experiments showed that Cu-Ni-S/Ni foam has a high removal rate of NOR (96.92%), wide pH adaptability (pH=4.0-10.0) and strong ion interference resistance (0.1-100 mmol/L). According to the Langmuir fitting model, the removal capacity can reach 417.4 mg/g at 25 °C, which is much higher than that of other water treatment agents reported in most studies. Characterization analysis indicated that the main removal mechanisms are surface complexation, cation bridging, electrostatic attraction, precipitation and flocculation. Transmission FTIR detection experiments showed that NOR on Cu-Ni-S/Ni foam has easily recognizable FTIR fingerprints; the intensity of characteristic peaks roughly reflects the concentration information to some extent. This semi-quantitative detection method has a wide linear range (5-100 mg/L) and a low limit of detection (4.6 mg/L). These results show that Cu-Ni-S/Ni foam has excellent removal performance and semi-quantitative detection ability of NOR molecules. This paper provides a new idea for designing and preparing multi-functional water treatment materials to achieve simultaneous removal and semi-quantitative detection of organic pollutants in water.

Keywords: adsorption-flocculation, antibiotics detection, Cu-Ni-S/Ni foam, norfloxacin

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Authors: Ahmed Mohammed Alsalama

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Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of the current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose a hybrid framework recommendation system to be applied on two-dimensional spaces (User x Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: data mining, association rules, recommendation systems, hybrid systems

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Authors: Dylan Santos De Pinho, Nabil Ouerhani

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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

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Authors: Qiuyi Lyu, Bin Gong

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Breadth-First Search(BFS) is a core graph algorithm that is widely used for graph analysis. As it is frequently used in many graph applications, improve the BFS performance is essential. In this paper, we present a graph ordering method that could reorder the graph nodes to achieve better data locality, thus, improving the BFS performance. Our method is based on an observation that the sibling relationships will dominate the cache access pattern during the BFS traversal. Therefore, we propose a frequency-based model to construct the graph order. First, we optimize the graph order according to the nodes’ visit frequency. Nodes with high visit frequency will be processed in priority. Second, we try to maximize the child nodes overlap layer by layer. As it is proved to be NP-hard, we propose a heuristic method that could greatly reduce the preprocessing overheads. We conduct extensive experiments on 16 real-world datasets. The result shows that our method could achieve comparable performance with the state-of-the-art methods while the graph ordering overheads are only about 1/15.

Keywords: breadth-first search, BFS, graph ordering, graph algorithm

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Jichi Wu

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Though fast fashion and consumption do boost the economy and push the progress of the industry, they have also caused a mass of waste, which has led to great pressure on the environment. This project mainly focuses on how to develop new sustainable textile and fashion design through recycling, upcycling, and reusing. Substantial field researches were implemented from the very beginning, including collecting reusable material from recycling centers. Hot-pressed composite materials, hand-cutting, and weaving were finally selected as the core material/method of this project after attempts and experiments. Four pieces of menswear, as well as hats and other decorative products made from wasted foams and fabrics, were successfully manufactured. Results show that foam is not only possible for furniture but also for clothing. It helps people to realize that foam is warm, heatproof, anti-slippery, and crease-resistant. So, all advantages could inspire people that even common materials could have new usage and are worthy of upcycling.

Keywords: sustainable design, foam, upcycling, life cycle, textile design

Procedia PDF Downloads 127

Authors: A. Karimzad Ghavidel, M. Zadshakouyan

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Laser cutting is a very common production method for cutting 2D polymeric parts. Developing of polymer composites with nano-fibers makes important their other properties like laser workability. The aim of this research is investigation of the influence different laser cutting conditions on the dimensional accuracy of parts and holes from poly methyl methacrylate (PMMA)/carbon nanotubes (CNTs) material. Experiments were carried out by considering of CNTs (in four level 0,0.5, 1 and 1.5% wt.%), laser power (60, 80, and 100 watt) and cutting speed 20, 30, and 40 mm/s as input variable factors. The results reveal that CNTs adding improves the laser workability of PMMA and the increasing of power has a significant effect on the part and hole size. The findings also show cutting speed is effective parameter on the size accuracy. Eventually, the statistical analysis of results was done, and calculated mathematical equations by the regression are presented for determining relation between input and output factor.

Keywords: dimensional accuracy, PMMA, CNTs, laser cutting

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Authors: Yilmaz Bayhan, Emin Güzel, Ömer Barış Özlüoymak, Ahmet İnce, Abdullah Sessiz

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In this study, determining of reduced tillage techniques in green bean farming as a second crop after harvesting wheat was targeted. To this aim, four different soil tillage methods namely, heavy-duty disc harrow (HD), rotary tiller (ROT), heavy-duty disc harrow plus rotary tiller (HD+ROT) and no-tillage (NT) (seeding by direct drill) were examined. Experiments were arranged in a randomized block design with three replications. The highest green beans yields were obtained in HD+ROT and NT as 5,862.1 and 5,829.3 Mg/ha, respectively. The lowest green bean yield was found in HD as 3,076.7 Mg/ha. The highest fuel consumption was measured 30.60 L ha^-1 for HD+ROT whereas the lowest value was found 7.50 L ha^-1 for NT. No tillage method gave the best results for fuel consumption and effective power requirement. It is concluded that no-tillage method can be used in second crop green bean in the Thrace Region due to economic and erosion conditions.

Keywords: green bean, soil tillage, yield, vegetative

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Authors: Liangliang Tang, Chang Xu, Xingying Chen

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GaInAsSb cells probably show better performance than GaSb cells in low-temperature thermophotovoltaic systems due to lower bandgap; however, few experiments proved this phenomenon so far. In this paper, numerical simulation is used to evaluate GaInAsSb and GaSb cells with similar structures under different radiation temperatures. We found that GaInAsSb cells with n-type emitters show slightly higher output power densities compared with that of GaSb cells with n-type emitters below 1,550 K-blackbody radiation, and the power density of the later cells will suppress the formers above this temperature point. During the temperature range of 1,000~2,000 K, the efficiencies of GaSb cells are about twice of GaInAsSb cells if perfect filters are used to prevent the emission of the non-absorbed long wavelength photons. Several parameters that affect the GaInAsSb cell were analyzed, such as doping profiles, thicknesses of GaInAsSb epitaxial layer and surface recombination velocity. The non-p junctions, i.e., n-type emitters are better for GaInAsSb cell fabrication, which is similar to that of GaSb cells.

Keywords: thermophotovoltaic cell, GaSb, GaInAsSb, diffused emitters

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Authors: M. Rezki, A. Belaidi

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This paper deals with a method of learning to solve a real problem in biomedical engineering from a technical study of muscle fatigue. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles (viewpoint: anatomical and physiological). EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain and muscle fatigue in general. In order to study the EMG signal for detecting fatigue in a muscle, we have taken a real problem which touches the tramway conductor the handle bar. For the study, we have used a typical autonomous platform in order to get signals at real time. In our case study, we were confronted with complex problem to do our experiments in a tram. This type of problem is recurring among students. To teach our students the method to solve this kind of problem, we built a similar system. Through this study, we realized a lot of objectives such as making the equipment for simulation, the study of detection of muscle fatigue and especially how to manage a study of biomedical looking.

Keywords: EMG, health platform, conductor’s tram, muscle fatigue

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Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier

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The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.

Keywords: control, identification, robot, co-manipulation, sensor-less

Procedia PDF Downloads 160

Authors: F. G Okibe, C. E Gimba, V. O Ajibola, I. G Ndukwe, E. D. Paul

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A full factorial experimental design technique at two levels and four factors (24) was used to optimize the adsorption at 615 nm of Xylene Cyanol ff in aqueous solutions onto activated carbon prepared from brachystegia eurycoma seed hulls by chemical carbonization method. The effect of pH (3 and 5), initial dye concentration (20 and 60 mg/l), adsorbent dosage (0.01 and 0.05 g), and contact time (30 and 60 min) on removal efficiency of the adsorbent for the dye were investigated at 298K. From the analysis of variance, response surface and cube plot, adsorbent dosage was observed to be the most significant factor affecting the adsorption process. However, from the interaction between the variables studied, the optimum removal efficiency was 96.80 % achieved with adsorbent dosage of 0.05 g, contact time 45 minutes, pH 3, and initial dye concentration 60 mg/l.

Keywords: factorial experimental design, adsorption, optimization, brachystegia eurycoma, xylene cyanol ff

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Authors: Abirami Baleswaran, Christel Couderc, Loubnah Belahcen, Jean Dayde, Hélène Tormo, Gwénaëlle Jard

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Cheeses are often reported to be spoiled by Pseudomonas spp., responsible for defects in appearance, texture, taste, and smell, leading to their non-marketing and even their destruction. Despite preventive actions, problems linked to Pseudomonas spp. are difficult to control by the lack of knowledge and control of these contaminants during the cheese manufacturing. Lactic goat cheese producers are not spared by this problem and are looking for solutions to decrease the number of spoiled cheeses. To explore different hypotheses, experiments are needed. However, cheese-making experiments at the pilot scale are expensive and time consuming. Thus, there is a real need to develop a miniature cheeses model system under controlled conditions. In a previous study, several miniature cheese models corresponding to different type of commercial cheeses have been developed for different purposes. The models were, for example, used to study the influence of milk, starters cultures, pathogen inhibiting additives, enzymatic reactions, microflora, freezing process on cheese. Nevertheless, no miniature model was described on the lactic goat cheese. The aim of this work was to develop a miniature cheese model system under controlled laboratory conditions which resembles commercial lactic goat cheese to study Pseudomonas spp. spoilage during the manufacturing and ripening process. First, a protocol for the preparation of miniature cheeses (3.5 times smaller than a commercial one) was designed based on the cheese factorymanufacturing process. The process was adapted from “Rocamadour” technology and involves maturation of pasteurized milk, coagulation, removal of whey by centrifugation, moulding, and ripening in a little scale cellar. Microbiological (total bacterial count, yeast, molds) and physicochemical (pH, saltinmoisture, moisture in fat-free)analyses were performed on four key stages of the process (before salting, after salting, 1st day of ripening, and end of ripening). Factory and miniature cheeses volatilomewere also obtained after full scan Sift-MS cheese analysis. Then, Pseudomonas spp. strains isolated from contaminated cheeses were selected on their origin, their ability to produce pigments, and their enzymatic activities (proteolytic, lecithinasic, and lipolytic). Factory and miniature curds were inoculated by spotting selected strains on the cheese surface. The expression of cheese spoilage was evaluated by counting the level of Pseudomonas spp. during the ripening and by visual observation and under UVlamp. The physicochemical and microbiological compositions of miniature cheeses permitted to assess that miniature process resembles factory process. As expected, differences involatilomes were observed, probably due to the fact that miniature cheeses are made usingpasteurized milk to better control the microbiological conditions and also because the little format of cheese induced probably a difference during the ripening even if the humidity and temperature in the cellar were quite similar. The spoilage expression of Pseudomonas spp. was observed in miniature and factory cheeses. It confirms that the proposed model is suitable for the preparation of miniature cheese specimens in the spoilage study of Pseudomonas spp. in lactic cheeses. This kind of model could be deployed for other applications and other type of cheese.

Keywords: cheese, miniature, model, pseudomonas spp, spoilage

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Authors: Aymen Laadhari, Gábor Székely

Abstract:

This paper is concerned with the development of a fully implicit and purely Eulerian fluid-structure interaction method tailored for the modeling of the large deformations of elastic membranes in a surrounding Newtonian fluid. We consider a simplified model for the mechanical properties of the membrane, in which the surface strain energy depends on the membrane stretching. The fully Eulerian description is based on the advection of a modified surface tension tensor, and the deformations of the membrane are tracked using a level set strategy. The resulting nonlinear problem is solved by a Newton-Raphson method, featuring a quadratic convergence behavior. A monolithic solver is implemented, and we report several numerical experiments aimed at model validation and illustrating the accuracy of the presented method. We show that stability is maintained for significantly larger time steps.

Keywords: finite element method, implicit, level set, membrane, Newton method

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Authors: A. J. Nazari, S. Honma

Abstract:

This paper evaluates oil displacement by water in Hauterivian sandstone reservoir of Kashkari oil field in North of Afghanistan. The core samples of this oil field were taken out from well No-21^st, and the relative permeability and fractional flow are analyzed. Steady state flow laboratory experiments are performed to empirically obtain the fractional flow curves and relative permeability in different water saturation ratio. The relative permeability represents the simultaneous flow behavior in the reservoir. The fractional flow approach describes the individual phases as fractional of the total flow. The fractional flow curve interprets oil displacement by water, and from the tangent of fractional flow curve can find out the average saturation behind the water front flow saturation. Therefore, relative permeability and fractional flow curves are suitable for describing the displacement of oil by water in a petroleum reservoir. The effects of irreducible water saturation, residual oil saturation on the displaceable amount of oil are investigated through Buckley-Leveret analysis.

Keywords: fractional flow, oil displacement, relative permeability, simultaneously flow

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Authors: Qihang Zeng, Wei Xu, Ying Shen, Changyuan Yu

Abstract:

In this paper, a highly sensitive fiber-optic curvature sensor based on four mode fiber (FMF) is presented and investigated. The proposed sensing structure is constructed by fusing a section of FMF into two standard single mode fibers (SMFs) concatenated with two no core fiber (NCF), i.e., SMF-NCF-FMF-NCF-SMF structure is fabricated. The length of the NCF is very short about 1 millimeter acting as exciting/recoupling the light from/into the core of the SMF, while the FMF is with 3 centimeters long supporting four eigenmodes including LP₀₁, LP₁₁, LP₂₁ and LP₀₂. High core modes in FMF can be effectively stimulated owing to mismatched mode field distribution and the mainly sensing principle is based on modal interferometer spectrum analysis. Different curvatures induce different strains on the FMF such that affecting the modal excitation, resulting spectrum shifts. One can get the curvature value by tracking the wavelength shifting. Experiments have been done to address the sensing performance, which is about 7.8 nm/m⁻¹ within a range of 1.90 m⁻¹~3.18 m⁻¹.

Keywords: curvature, four mode fiber, highly sensitive, modal interferometer

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Authors: Anuar Mohd Salleh, Mohd Effendi Daud

Abstract:

This study presents a kinematic positioning approach which is use the GPS buoy for precise ocean surface monitoring. A GPS buoy data from two experiments have been processed using a precise, medium-range differential kinematic technique. In each case the data were collected for more than 24 hours at nearby coastal site at a high rate (1 Hz), along with measurements from neighboring tidal stations, to verify the estimated sea surface heights. Kinematic coordinates of GPS buoy were estimated using the epoch-wise pre-elimination and the backward substitution algorithm. Test results show the centimeter level accuracy in sea surface height determination can be successfully achieved using proposed technique. The centimeter level agreement between two methods also suggests the possibility of using this inexpensive and more flexible GPS buoy equipment to enhance (or even replace) the current use of tidal gauge stations.

Keywords: global positioning system, kinematic GPS, sea surface height, GPS buoy, tide gauge

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Authors: Jovana Grahovac, Ivana Pajcin, Natasa Lukic, Jelena Dodic, Aleksandar Jokic

Abstract:

To obtain purified biomass to be used in the plant pathogen biocontrol or as soil biofertilizer, it is necessary to eliminate residual broth components at the end of the fermentation process. The main drawback of membrane separation techniques is permeate flux decline due to the membrane fouling. Fouling mitigation measures increase the pressure drop along membrane channel due to the increased resistance to flow of the feed suspension, thus increasing the hydraulic power drop. At the same time, these measures lead to an increase in the permeate flux due to the reduced resistance of the filtration cake on the membrane surface. Because of these opposing effects, the energy efficiency of fouling mitigation measures is limited, and the justification of its application is provided by information on a reducing specific energy consumption compared to a case without any measures employed. In this study, the influence of static mixer (Kenics) and air-sparging (two-phase flow) on reduction of specific energy consumption (ER) was investigated. Cultivation Bacillus velezensis was carried out in the 3-L bioreactor (Biostat® Aplus) containing 2 L working volume with two parallel Rushton turbines and without internal baffles. Cultivation was carried out at 28 °C on at 150 rpm with an aeration rate of 0.75 vvm during 96 h. The experiments were carried out in a conventional cross-flow microfiltration unit. During experiments, permeate and retentate were recycled back to the broth vessel to simulate continuous process. The single channel ceramic membrane (TAMI Deutschland) used had a nominal pore size 200 nm with the length of 250 mm and an inner/external diameter of 6/10 mm. The useful membrane channel surface was 4.33×10⁻³ m². Air sparging was brought by the pressurized air connected by a three-way valve to the feed tube by a simple T-connector without diffusor. The different approaches to flux improvement are compared in terms of energy consumption. Reduction of specific energy consumption compared to microfiltration without fouling mitigation is around 49% and 63%, for use of two-phase flow and a static mixer, respectively. In the case of a combination of these two fouling mitigation methods, ER is 60%, i.e., slightly lower compared to the use of turbulence promoter alone. The reason for this result can be found in the fact that flux increase is more affected by the presence of a Kenics static mixer while sparging results in an increase of energy used during microfiltration. By comparing combined method with turbulence promoter flux enhancement method ER is negative (-7%) which can be explained by increased power consumption for air flow with moderate contribution to the flux increase. Another confirmation for this fact can be found by comparing energy consumption values for combined method with energy consumption in the case of two-phase flow. In this instance energy reduction (ER) is 22% that demonstrates that turbulence promoter is more efficient compared to two phase flow. Antimicrobial activity of Bacillus velezensis biomass against phytopathogenic isolates Xanthomonas campestris was preserved under different fouling reduction methods.

Keywords: Bacillus velezensis, microfiltration, static mixer, two-phase flow

Procedia PDF Downloads 118