Search results for: laser processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4508

Search results for: laser processing

3338 Dual Ion-Crosslinking Human Keratin Based Bioink for 3D Bioprinting

Authors: Jae Seo Lee, Il Keun Kwon

Abstract:

In the last decades, keratin-based on natural extracts has considerably increased interest as a skin tissue regeneration. However, most parts of keratin had a limitation to 3D scaffolds due to low biological affinity and general low mechanical properties. To create a 3D structure, a facile bioink was designed with a photocurable crosslinking stage system using natural polymer-based human keratin. Keratin-based bioink enables the crosslinking more quickly through two types of photo and ion crosslinking for module engineering assembly. Rheological results showed that keratin-based bioink with high concentration possessed superior mechanical rigidity for 3D bioprinting. Different 3D geometrically constructs were successfully fabricated with optimal bioprinting parameters through the 3D printer with X-Y-Z controlled UV laser system. The presented study has offered a distinct advantage for 3D printing of keratin-based hydrogel into 3D complex-shaped biomimetic constructs. Thus, keratin-based bioink opens up new avenues in bioprinting to directly substitute tissue or organs.

Keywords: human keratin, hydrogel, ion-crosslinking, 3D bioprinting

Procedia PDF Downloads 128
3337 Exploring Structure of Human Chromosomes Using Fluorescence Lifetime Imaging

Authors: A. Bhartiya, S. Botchway, M. Yusuf, I. Robinson

Abstract:

Chromatin condensation is maintained by DNA-based proteins and some divalent cations (Mg²⁺, Ca²⁺, etc.). Condensation process during cell division maintains structural and functional organizations of chromosomes by transferring genetic information correctly to daughter cells. Fluorescence Lifetime Imaging (FLIM) technique measures the fluorescence decay of fixed human chromosomes by calculating the lifetime of fluorophores at a pixel x of the arrival of each photon as a function of time delay t, following excitation with a laser pulse. Fixed metaphase human chromosomes were labelled with DNA-binding dye, DAPI and later DAPI fluorescence lifetime measured using multiphoton microscopy. 5 out of 23 pairs of human chromosomes shown shorter lifetime at the centromere region, differentiating proportion of compaction along the length of chromosomes. Different lifetime was observed in a condensed and de-condensed chromosome. It clearly indicates the involvement of divalent cations in the process of condensation.

Keywords: divalent cations, FLIM (Fluorescence Lifetime Imaging), human chromosomes, multiphoton microscopy

Procedia PDF Downloads 291
3336 Distributed Processing for Content Based Lecture Video Retrieval on Hadoop Framework

Authors: U. S. N. Raju, Kothuri Sai Kiran, Meena G. Kamal, Vinay Nikhil Pabba, Suresh Kanaparthi

Abstract:

There is huge amount of lecture video data available for public use, and many more lecture videos are being created and uploaded every day. Searching for videos on required topics from this huge database is a challenging task. Therefore, an efficient method for video retrieval is needed. An approach for automated video indexing and video search in large lecture video archives is presented. As the amount of video lecture data is huge, it is very inefficient to do the processing in a centralized computation framework. Hence, Hadoop Framework for distributed computing for Big Video Data is used. First, step in the process is automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. In the next step, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames. The OCR and detected slide text line types are adopted for keyword extraction, by which both video- and segment-level keywords are extracted for content-based video browsing and search. The performance of the indexing process can be improved for a large database by using distributed computing on Hadoop framework.

Keywords: video lectures, big video data, video retrieval, hadoop

Procedia PDF Downloads 538
3335 Effect of Temperature and Deformation Mode on Texture Evolution of AA6061

Authors: M. Ghosh, A. Miroux, L. A. I. Kestens

Abstract:

At molecular or micrometre scale, practically all materials are neither homogeneous nor isotropic. The concept of texture is used to identify the structural features that cause the properties of a material to be anisotropic. For metallic materials, the anisotropy of the mechanical behaviour originates from the crystallographic nature of plastic deformation, and is therefore controlled by the crystallographic texture. Anisotropy in mechanical properties often constitutes a disadvantage in the application of materials, as it is often illustrated by the earing phenomena during drawing. However, advantages may also be attained when considering other properties (e.g. optimization of magnetic behaviour to a specific direction) by controlling texture through thermo-mechanical processing). Nevertheless, in order to have better control over the final properties it is essential to relate texture with materials processing route and subsequently optimise their performance. However, up to date, few studies have been reported about the evolution of texture in 6061 aluminium alloy during warm processing (from room temperature to 250ºC). In present investigation, recrystallized 6061 aluminium alloy samples were subjected to tensile and plane strain compression (PSC) at room and warm temperatures. The gradual change of texture following both deformation modes were measured and discussed. Tensile tests demonstrate the mechanism at low strain while PSC does the same at high strain and eventually simulate the condition of rolling. Cube dominated texture of the initial rolled and recrystallized AA6061 sheets were replaced by domination of S and R components after PSC at room temperature, warm temperature (250ºC) though did not reflect any noticeable deviation from room temperature observation. It was also noticed that temperature has no significant effect on the evolution of grain morphology during PSC. The band contrast map revealed that after 30% deformation the substructure inside the grain is mainly made of series of parallel bands. A tendency for decrease of Cube and increase of Goss was noticed after tensile deformation compared to as-received material. Like PSC, texture does not change after deformation at warm temperature though. n-fibre was noticed for all the three textures from Goss to Cube.

Keywords: AA 6061, deformation, temperature, tensile, PSC, texture

Procedia PDF Downloads 487
3334 Experimental Modeling of Spray and Water Sheet Formation Due to Wave Interactions with Vertical and Slant Bow-Shaped Model

Authors: Armin Bodaghkhani, Bruce Colbourne, Yuri S. Muzychka

Abstract:

The process of spray-cloud formation and flow kinematics produced from breaking wave impact on vertical and slant lab-scale bow-shaped models were experimentally investigated. Bubble Image Velocimetry (BIV) and Image Processing (IP) techniques were applied to study the various types of wave-model impacts. Different wave characteristics were generated in a tow tank to investigate the effects of wave characteristics, such as wave phase velocity, wave steepness on droplet velocities, and behavior of the process of spray cloud formation. The phase ensemble-averaged vertical velocity and turbulent intensity were computed. A high-speed camera and diffused LED backlights were utilized to capture images for further post processing. Various pressure sensors and capacitive wave probes were used to measure the wave impact pressure and the free surface profile at different locations of the model and wave-tank, respectively. Droplet sizes and velocities were measured using BIV and IP techniques to trace bubbles and droplets in order to measure their velocities and sizes by correlating the texture in these images. The impact pressure and droplet size distributions were compared to several previously experimental models, and satisfactory agreements were achieved. The distribution of droplets in front of both models are demonstrated. Due to the highly transient process of spray formation, the drag coefficient for several stages of this transient displacement for various droplet size ranges and different Reynolds number were calculated based on the ensemble average method. From the experimental results, the slant model produces less spray in comparison with the vertical model, and the droplet velocities generated from the wave impact with the slant model have a lower velocity as compared with the vertical model.

Keywords: spray charachteristics, droplet size and velocity, wave-body interactions, bubble image velocimetry, image processing

Procedia PDF Downloads 302
3333 Data Clustering in Wireless Sensor Network Implemented on Self-Organization Feature Map (SOFM) Neural Network

Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

Abstract:

Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

Procedia PDF Downloads 520
3332 Thermal Annealing Effects on Nonradiative Recombination Parameters of GaInAsSb/GaSb by Means of Photothermal Defection Technique

Authors: Souha Bouagila, Soufiene Ilahi, Noureddine Yacoubi

Abstract:

We have used Photothermal deflection spectroscopy PTD to investigate the impact of thermal annealing on electronics properties of GaInAsSb/GaSb.GaInAsSb used as an active layer for Vertical Cavity Surface Emitting laser (VCSEL). We have remarked that surface recombination velocity (SRV) from 7963 m / s (± 6.3%) to 1450 m / s (± 3.6) for as grown to sample annealed for 60 min. Accordingly, Force Microscopy images analyses agree well with the measure of surface recombination velocity. We have found that Root-Mean-Square Roughness (RMS) decreases as respect of annealing time. In addition, we have that the diffusion length and minority carrier mobility have been enhanced according to annealing time. However, due to annealing effects, the interface recombination velocity (IRV) is increased from 1196 m / s (± 5) to 6000 m/s (5%) for GaInAsSb in respect of annealed times.

Keywords: nonradiative lifetime, mobility of minority carrier, diffusion length, Surface and interface recombination velocity

Procedia PDF Downloads 75
3331 Machine Learning Approach for Mutation Testing

Authors: Michael Stewart

Abstract:

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

Procedia PDF Downloads 204
3330 Development of a Weed Suppression Robot for Rice Cultivation Weed Suppression and Posture Control

Authors: Shohei Nakai, Yasuhiro Yamada

Abstract:

Weed suppression and weeding are necessary measures for rice cultivation. Weed suppression precedes the process of weeding. It means suppressing the growth of young weeds and creating a weed-less environment. If we suppress the growth of weeds, we can reduce the number of weeds in a paddy field. This would result in a reduction of the weeding work load. In this paper, we will show how we developed a weed suppression robot for the purpose of reducing the weeding work load. The robot has a laser range finder for autonomous mobility and a robot arm for weed suppression. It travels along the rice rows without stepping on and injuring the rice plants in a paddy field. The robot arm applies force to the weed seedlings and thereby suppresses the growth of weeds. This paper will explain the methodology of the autonomous mobile, the experiment in weed suppression, and the method of controlling the robot’s posture on uneven ground.

Keywords: mobile robot, paddy field, robot arm, weed

Procedia PDF Downloads 381
3329 Mage Fusion Based Eye Tumor Detection

Authors: Ahmed Ashit

Abstract:

Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

Procedia PDF Downloads 367
3328 Identification of EEG Attention Level Using Empirical Mode Decompositions for BCI Applications

Authors: Chia-Ju Peng, Shih-Jui Chen

Abstract:

This paper proposes a method to discriminate electroencephalogram (EEG) signals between different concentration states using empirical mode decomposition (EMD). Brain-computer interface (BCI), also called brain-machine interface, is a direct communication pathway between the brain and an external device without the inherent pathway such as the peripheral nervous system or skeletal muscles. Attention level is a common index as a control signal of BCI systems. The EEG signals acquired from people paying attention or in relaxation, respectively, are decomposed into a set of intrinsic mode functions (IMF) by EMD. Fast Fourier transform (FFT) analysis is then applied to each IMF to obtain the frequency spectrums. By observing power spectrums of IMFs, the proposed method has the better identification of EEG attention level than the original EEG signals between different concentration states. The band power of IMF3 is the most obvious especially in β wave, which corresponds to fully awake and generally alert. The signal processing method and results of this experiment paves a new way for BCI robotic system using the attention-level control strategy. The integrated signal processing method reveals appropriate information for discrimination of the attention and relaxation, contributing to a more enhanced BCI performance.

Keywords: biomedical engineering, brain computer interface, electroencephalography, rehabilitation

Procedia PDF Downloads 394
3327 Bit Error Rate Monitoring for Automatic Bias Control of Quadrature Amplitude Modulators

Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

Abstract:

The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

Procedia PDF Downloads 193
3326 Application of Laser-Induced Breakdown Spectroscopy for the Evaluation of Concrete on the Construction Site and in the Laboratory

Authors: Gerd Wilsch, Tobias Guenther, Tobias Voelker

Abstract:

In view of the ageing of vital infrastructure facilities, a reliable condition assessment of concrete structures is becoming of increasing interest for asset owners to plan timely and appropriate maintenance and repair interventions. For concrete structures, reinforcement corrosion induced by penetrating chlorides is the dominant deterioration mechanism affecting the serviceability and, eventually, structural performance. The determination of the quantitative chloride ingress is required not only to provide valuable information on the present condition of a structure, but the data obtained can also be used for the prediction of its future development and associated risks. At present, wet chemical analysis of ground concrete samples by a laboratory is the most common test procedure for the determination of the chloride content. As the chloride content is expressed by the mass of the binder, the analysis should involve determination of both the amount of binder and the amount of chloride contained in a concrete sample. This procedure is laborious, time-consuming, and costly. The chloride profile obtained is based on depth intervals of 10 mm. LIBS is an economically viable alternative providing chloride contents at depth intervals of 1 mm or less. It provides two-dimensional maps of quantitative element distributions and can locate spots of higher concentrations like in a crack. The results are correlated directly to the mass of the binder, and it can be applied on-site to deliver instantaneous results for the evaluation of the structure. Examples for the application of the method in the laboratory for the investigation of diffusion and migration of chlorides, sulfates, and alkalis are presented. An example for the visualization of the Li transport in concrete is also shown. These examples show the potential of the method for a fast, reliable, and automated two-dimensional investigation of transport processes. Due to the better spatial resolution, more accurate input parameters for model calculations are determined. By the simultaneous detection of elements such as carbon, chlorine, sodium, and potassium, the mutual influence of the different processes can be determined in only one measurement. Furthermore, the application of a mobile LIBS system in a parking garage is demonstrated. It uses a diode-pumped low energy laser (3 mJ, 1.5 ns, 100 Hz) and a compact NIR spectrometer. A portable scanner allows a two-dimensional quantitative element mapping. Results show the quantitative chloride analysis on wall and floor surfaces. To determine the 2-D distribution of harmful elements (Cl, C), concrete cores were drilled, split, and analyzed directly on-site. Results obtained were compared and verified with laboratory measurements. The results presented show that the LIBS method is a valuable addition to the standard procedures - the wet chemical analysis of ground concrete samples. Currently, work is underway to develop a technical code of practice for the application of the method for the determination of chloride concentration in concrete.

Keywords: chemical analysis, concrete, LIBS, spectroscopy

Procedia PDF Downloads 108
3325 Process Optimization and Microbial Quality of Provitamin A-Biofortified Amahewu, a Non-Alcoholic Maize Based Beverage

Authors: Temitope D. Awobusuyi, Eric O. Amonsou, Muthulisi Siwela, Oluwatosin A. Ijabadeniyi

Abstract:

Provitamin A-biofortified maize has been developed to alleviate Vitamin A deficiency; a major public health problem in developing countries. Amahewu, a non-alcoholic fermented maize based beverage is produced using white maize, which is deficient in Vitamin A. In this study, the suitable processing conditions for the production of amahewu using provitamin A-biofortified maize and the microbial quality of the processed products were evaluated. Provitamin A-biofortified amahewu was produced with reference to traditional processing method. Processing variables were Inoculum types (Malted provitamin A maize, Wheat bran, and lactobacillus mixed starter culture with either malted provitamin A or wheat bran) and concentration (0.5 %, 1 % and 2 %). A total of four provitamin A-biofortified amahewu products after fermentation were subjected to different storage conditions: 4ᴼC, 25ᴼC and 37ᴼC. pH and TTA were monitored throughout the storage period. Sample of provitamin A-biofortified amahewu were plated and observed every day for 5 days to assess the presence of Aerobic and Anaerobic spore formers, E.coli, Lactobacillus and Mould. The addition of starter culture substantially reduced the fermentation time (6 hour, pH 3.3) compared to those with no addition of starter culture (24 hour pH 3.5). It was observed that Lactobacillus were present from day 0 for all the storage temperatures. The presence of aerobic spore former and mould were observed on day 3. E.coli and Anaerobic spore formers were not present throughout the storage period. These microbial growth were minimal at 4ᴼC while 25ᴼC had higher counts of growth with 37ᴼC having the highest colony count. Throughout the storage period, pH of provitamin A-biofortified amahewu was stable. Provitamin A-biofortified amahewu stored under refrigerated condition (4ᴼC) had better storability compared to 25ᴼC and 37ᴼC. The production and microbial quality of provitamin A-biofortified amahewu might be important in combating Vitamin A Deficiency.

Keywords: biofortification, fermentation, maize, vitamin A deficiency

Procedia PDF Downloads 436
3324 Predicting Polyethylene Processing Properties Based on Reaction Conditions via a Coupled Kinetic, Stochastic and Rheological Modelling Approach

Authors: Kristina Pflug, Markus Busch

Abstract:

Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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3323 The Diagnostic Utility and Sensitivity of the Xpert® MTB/RIF Assay in Diagnosing Mycobacterium tuberculosis in Bone Marrow Aspirate Specimens

Authors: Nadhiya N. Subramony, Jenifer Vaughan, Lesley E. Scott

Abstract:

In South Africa, the World Health Organisation estimated 454000 new cases of Mycobacterium tuberculosis (M.tb) infection (MTB) in 2015. Disseminated tuberculosis arises from the haematogenous spread and seeding of the bacilli in extrapulmonary sites. The gold standard for the detection of MTB in bone marrow is TB culture which has an average turnaround time of 6 weeks. Histological examinations of trephine biopsies to diagnose MTB also have a time delay owing mainly to the 5-7 day processing period prior to microscopic examination. Adding to the diagnostic delay is the non-specific nature of granulomatous inflammation which is the hallmark of MTB involvement of the bone marrow. A Ziehl-Neelson stain (which highlights acid-fast bacilli) is therefore mandatory to confirm the diagnosis but can take up to 3 days for processing and evaluation. Owing to this delay in diagnosis, many patients are lost to follow up or remain untreated whilst results are awaited, thus encouraging the spread of undiagnosed TB. The Xpert® MTB/RIF (Cepheid, Sunnyvale, CA) is the molecular test used in the South African national TB program as the initial diagnostic test for pulmonary TB. This study investigates the optimisation and performance of the Xpert® MTB/RIF on bone marrow aspirate specimens (BMA), a first since the introduction of the assay in the diagnosis of extrapulmonary TB. BMA received for immunophenotypic analysis as part of the investigation into disseminated MTB or in the evaluation of cytopenias in immunocompromised patients were used. Processing BMA on the Xpert® MTB/RIF was optimised to ensure bone marrow in EDTA and heparin did not inhibit the PCR reaction. Inactivated M.tb was spiked into the clinical bone marrow specimen and distilled water (as a control). A volume of 500mcl and an incubation time of 15 minutes with sample reagent were investigated as the processing protocol. A total of 135 BMA specimens had sufficient residual volume for Xpert® MTB/RIF testing however 22 specimens (16.3%) were not included in the final statistical analysis as an adequate trephine biopsy and/or TB culture was not available. Xpert® MTB/RIF testing was not affected by BMA material in the presence of heparin or EDTA, but the overall detection of MTB in BMA was low compared to histology and culture. Sensitivity of the Xpert® MTB/RIF compared to both histology and culture was 8.7% (95% confidence interval (CI): 1.07-28.04%) and sensitivity compared to histology only was 11.1% (95% CI: 1.38-34.7%). Specificity of the Xpert® MTB/RIF was 98.9% (95% CI: 93.9-99.7%). Although the Xpert® MTB/RIF generates a faster result than histology and TB culture and is less expensive than culture and drug susceptibility testing, the low sensitivity of the Xpert® MTB/RIF precludes its use for the diagnosis of MTB in bone marrow aspirate specimens and warrants alternative/additional testing to optimise the assay.

Keywords: bone marrow aspirate , extrapulmonary TB, low sensitivity, Xpert® MTB/RIF

Procedia PDF Downloads 175
3322 Production and Evaluation of Mango Pulp by Using Ohmic Heating Process

Authors: Sobhy M. Mohsen, Mohamed M. El-Nikeety, Tarek G. Mohamed, Michael Murkovic

Abstract:

The present work aimed to study the use of ohmic heating in the processing of mango pulp comparing to conventional method. Mango pulp was processed by using ohmic heating under the studied suitable conditions. Physical, chemical and microbiological properties of mango pulp were studied. The results showed that processing of mango pulp by using either ohmic heating or conventional method caused a decrease in the contents of TSS, total carbohydrates, total acidity, total sugars (reducing and non-reducing sugar) and an increase in phenol content, ascorbic acid and carotenoids compared to the conventional process. The increase in electric conductivity of mango pulp during ohmic heating was due to the addition of some electrolytes (salts) to increase the ions and enhance the process. The results also indicate that mango pulp processed by ohmic heating contained more phenols, carbohydrates and vitamin C and less HMF compared to that produced by conventional one. Total pectin and its fractions had slightly reduced by ohmic heating compared to conventional method. Enzymatic activities showed a reduction in poly phenoloxidase (PPO) and polygalacturonase (PG) activity in mango pulp processed by conventional method. However, ohmic heating completely inhibited PPO and PG activities.

Keywords: ohmic heating, mango pulp, phenolic, sarotenoids

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3321 Use of the Gas Chromatography Method for Hydrocarbons' Quality Evaluation in the Offshore Fields of the Baltic Sea

Authors: Pavel Shcherban, Vlad Golovanov

Abstract:

Currently, there is an active geological exploration and development of the subsoil shelf of the Kaliningrad region. To carry out a comprehensive and accurate assessment of the volumes and degree of extraction of hydrocarbons from open deposits, it is necessary to establish not only a number of geological and lithological characteristics of the structures under study, but also to determine the oil quality, its viscosity, density, fractional composition as accurately as possible. In terms of considered works, gas chromatography is one of the most capacious methods that allow the rapid formation of a significant amount of initial data. The aspects of the application of the gas chromatography method for determining the chemical characteristics of the hydrocarbons of the Kaliningrad shelf fields are observed in the article, as well as the correlation-regression analysis of these parameters in comparison with the previously obtained chemical characteristics of hydrocarbon deposits located on the land of the region. In the process of research, a number of methods of mathematical statistics and computer processing of large data sets have been applied, which makes it possible to evaluate the identity of the deposits, to specify the amount of reserves and to make a number of assumptions about the genesis of the hydrocarbons under analysis.

Keywords: computer processing of large databases, correlation-regression analysis, hydrocarbon deposits, method of gas chromatography

Procedia PDF Downloads 159
3320 Virtual 3D Environments for Image-Based Navigation Algorithms

Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

Abstract:

This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

Procedia PDF Downloads 260
3319 Thermal Annealing Effects on Minority Carrier Lifetime in GaInAsSb/GaSb by Means of Photothermal Defletion Technique

Authors: Souha Bouagila, Soufiene Ilahi

Abstract:

Photothermal deflection technique PTD have been employed to study the impact of thermal annealing on minority carrier in GaInAsSb grown on GaSb substarte, which used as an active layer for Vertical Cavity Surface Emitting laser (VCSEL). Photothermal defelction technique is nondescructive and accurate technique for electronics parameters determination. The measure of non-radiative recombination, electronic diffusivity, surface and interface recombination are effectuated by fitting the theoretical PTD signal to the experimental ones. As a results, we have found that Non-radiative lifetime increases from 3.8 µs (± 3, 9 %) for not annealed GaInAsSb to the 7.1 µs (± 5, 7%). In fact, electronic diffusivity D increased from 60.1 (± 3.9 %) to 89.6 cm2 / s (± 2.7%) for the as grown to that annealed for 60 min respectively. We have remarked that surface recombination velocity (SRV) decreases from 7963 m / s (± 6.3%) to 1450 m / s (± 3.6).

Keywords: nonradiative lifetime, mobility of minority carrier, diffusion length, Surface and interface recombination velocity.GaInAsSb active layer

Procedia PDF Downloads 70
3318 3D Building Model Utilizing Airborne LiDAR Dataset and Terrestrial Photographic Images

Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

Abstract:

The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

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3317 Advances in the Design of Wireless Sensor Networks for Environmental Monitoring

Authors: Shathya Duobiene, Gediminas Račiukaitis

Abstract:

Wireless Sensor Networks (WSNs) are an emerging technology that opens up a new field of research. The significant advance in WSN leads to an increasing prevalence of various monitoring applications and real-time assistance in labs and factories. Selective surface activation induced by laser (SSAIL) is a promising technology that adapts to the WSN design freedom of shape, dimensions, and material. This article proposes and implements a WSN-based temperature and humidity monitoring system, and its deployed architectures made for the monitoring task are discussed. Experimental results of newly developed sensor nodes implemented in university campus laboratories are shown. Then, the simulation and the implementation results obtained through monitoring scenarios are displayed. At last, a convenient solution to keep the WSN alive and functional as long as possible is proposed. Unlike other existing models, on success, the node is self-powered and can utilise minimal power consumption for sensing and data transmission to the base station.

Keywords: IoT, network formation, sensor nodes, SSAIL technology

Procedia PDF Downloads 93
3316 Effect of the Deposition Time of Hydrogenated Nanocrystalline Si Grown on Porous Alumina Film on Glass Substrate by Plasma Processing Chemical Vapor Deposition

Authors: F. Laatar, S. Ktifa, H. Ezzaouia

Abstract:

Plasma Enhanced Chemical Vapor Deposition (PECVD) method is used to deposit hydrogenated nanocrystalline silicon films (nc-Si: H) on Porous Anodic Alumina Films (PAF) on glass substrate at different deposition duration. Influence of the deposition time on the physical properties of nc-Si: H grown on PAF was investigated through an extensive correlation between micro-structural and optical properties of these films. In this paper, we present an extensive study of the morphological, structural and optical properties of these films by Atomic Force Microscopy (AFM), X-Ray Diffraction (XRD) techniques and a UV-Vis-NIR spectrometer. It was found that the changes in DT can modify the films thickness, the surface roughness and eventually improve the optical properties of the composite. Optical properties (optical thicknesses, refractive indexes (n), absorption coefficients (α), extinction coefficients (k), and the values of the optical transitions EG) of this kind of samples were obtained using the data of the transmittance T and reflectance R spectra’s recorded by the UV–Vis–NIR spectrometer. We used Cauchy and Wemple–DiDomenico models for the analysis of the dispersion of the refractive index and the determination of the optical properties of these films.

Keywords: hydragenated nanocrystalline silicon, plasma processing chemical vapor deposition, X-ray diffraction, optical properties

Procedia PDF Downloads 383
3315 Sarcasm Recognition System Using Hybrid Tone-Word Spotting Audio Mining Technique

Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

Abstract:

Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

Procedia PDF Downloads 295
3314 Synthesis of Silver Powders Destined for Conductive Paste Metallization of Solar Cells Using Butyl-Carbitol and Butyl-Carbitol Acetate Chemical Reduction

Authors: N. Moudir, N. Moulai-Mostefa, Y. Boukennous, I. Bozetine, N. Kamel, D. Moudir

Abstract:

the study focuses on a novel process of silver powders synthesis for the preparation of conductive pastes used for solar cells metalization. Butyl-Carbitol and butyl-carbitol Acetate have been used as solvents and reducing agents of silver nitrate (AgNO3) as precursor to get silver powders. XRD characterization revealed silver powders with a cubic crystal system. SEM micro graphs showed spherical morphology of the particles. Laser granulometer gives similar particles distribution for the two agents. Using same glass frit and organic vehicle for comparative purposes, two conductive pastes were prepared with the synthesized silver powders for the front-side metalization of multi-crystalline cells. The pastes provided acceptable fill factor of 59.5 % and 60.8 % respectively.

Keywords: chemical reduction, conductive paste, silver nitrate, solar cell

Procedia PDF Downloads 308
3313 Building an Ontology for Researchers: An Application of Topic Maps and Social Information

Authors: Yu Hung Chiang, Hei Chia Wang

Abstract:

In the academic area, it is important for research to find proper research domain. Many researchers may refer to conference issues to find their interesting or new topics. Furthermore, conferences issues can help researchers realize current research trends in their field and learn about cutting-edge developments in their specialty. However, online published conference information may widely be distributed; it is not easy to be concluded. Many researchers use search engine of journals or conference issues to filter information in order to get what they want. However, this search engine has its limitation. There will still be some issues should be considered; i.e. researchers cannot find the associated topics which may be useful information for them. Hence, use Knowledge Management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted; but most existed ontology construction methods do not consider social information between target users. To effective in academic KM, this study proposes a method of constructing research Topic Maps using Open Directory Project (ODP) and Social Information Processing (SIP). Through catching of social information in conference website: i.e. the information of co-authorship or collaborator, research topics can be associated among related researchers. Finally, the experiments show Topic Maps successfully help researchers to find the information they need more easily and quickly as well as construct associations between research topics.

Keywords: knowledge management, topic map, social information processing, ontology extraction

Procedia PDF Downloads 294
3312 Techno-Economic Analysis (TEA) of Circular Economy Approach in the Valorisation of Pig Meat Processing Wastes

Authors: Ribeiro A., Vilarinho C., Luisa A., Carvalho J

Abstract:

The pig meat industry generates large volumes of by- and co-products like blood, bones, skin, trimmings, organs, viscera, and skulls, among others, during slaughtering and meat processing and must be treated and disposed of ecologically. The yield of these by-products has been reported to account for about 10% to 15% of the value of the live animal in developed countries, although animal by-products account for about two-thirds of the animal after slaughter. It was selected for further valorization of the principal wastes produced throughout the value chain of pig meat production: Pig Manure, Pig Bones, Fats, Skins, Pig Hair, Wastewater, Wastewater sludges, and other animal subproducts type III. According to the potential valorization options, these wastes will be converted into Biomethane, Fertilizers (phosphorus and digestate), Hydroxyapatite, and protein hydrolysates (Keratin and Collagen). This work includes comprehensive technical and economic analyses (TEA) for each valorization route or applied technology. Metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), and payback periods were used to evaluate economic feasibility. From this analysis, it can be concluded that, for Biogas Production, the scenarios using pig manure, wastewater sludges and mixed grass and leguminous wastes presented a remarkably high economic feasibility. Scenarios showed high economic feasibility with a positive payback period, NPV, and IRR. The optimal scenario combining pig manure with mixed grass and leguminous wastes had a payback period of 1.2 years and produced 427,6269 m³ of biomethane annually. Regarding the Chemical Extraction of Phosphorous and Nitrogen, results proved that the process is economically unviable due to negative cash flows despite high recovery rates. The TEA of Hydrolysis and Extraction of Keratin Hydrolysates indicate that a unit processing and valorizing 10 tons of pig hair per year for the production of keratin hydrolysate has an NPV of 907,940 €, an IRR of 13.07%, and a Payback period of 5.41 years. All of these indicators suggest a highly potential project to explore in the future. On the opposite, the results of Hydrolysis and Extraction of Collagen Hydrolysates showed a process economically unviable with negative cash flows in all scenarios due to the high-fat content in raw materials. In fact, the results from the valorization of 10 tons of pig skin had a negative cash flow of 453 743,88 €. TEA results of Extraction and purification of Hydroxyapatite from Pig Bones with Pyrolysis indicate that unit processing and valorizing 10 tons of pig bones per year for the production of hydroxyapatite has an NPV of 1 274 819,00 €, an IRR of 65.43%, and a Payback period of 1,5 years over a timeline of 10 years with a discount rate of 10%. These valorization routes, circular economy and bio-refinery approach offer significant contributions to sustainable bio-based operations within the agri-food industry. This approach transforms waste into valuable resources, enhancing both environmental and economic outcomes and contributing to a more sustainable and circular bioeconomy.

Keywords: techno-economic analysis (TEA), pig meat processing wastes, circular economy, bio-refinery

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3311 FLIME - Fast Low Light Image Enhancement for Real-Time Video

Authors: Vinay P., Srinivas K. S.

Abstract:

Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

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3310 Image Processing-Based Maize Disease Detection Using Mobile Application

Authors: Nathenal Thomas

Abstract:

In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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3309 Railway Process Automation to Ensure Human Safety with the Aid of IoT and Image Processing

Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

Abstract:

Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

Procedia PDF Downloads 180