Search results for: particle tracking microrheology

Authors: Kyoungrean Kim

Abstract:

Importance of deep-sea mineral resources is dramatically increasing due to the depletion of land mineral resources corresponding to increasing human’s economic activities. Korea has acquired exclusive exploration licenses at four areas which are the Clarion-Clipperton Fracture Zone in the Pacific Ocean (2002), Tonga (2008), Fiji (2011) and Indian Ocean (2014). The preparation for commercial mining of Nautilus minerals (Canada) and Lockheed martin minerals (USA) is expected by 2020. The London Protocol 1996 (LP) under International Maritime Organization (IMO) and International Seabed Authority (ISA) will set environmental guidelines for deep-sea mining until 2020, to protect marine environment. In this research, the applicability of washing/extraction treatment for the remediation of deep-sea mining tailings was mainly evaluated in order to present preliminary data to develop practical remediation technology in near future. Polymetallic nodule samples were collected at the Clarion-Clipperton Fracture Zone in the Pacific Ocean, then stored at room temperature. Samples were pulverized by using jaw crusher and ball mill then, classified into 3 particle sizes (> 63 µm, 63-20 µm, < 20 µm) by using vibratory sieve shakers (Analysette 3 Pro, Fritsch, Germany) with 63 µm and 20 µm sieve. Only the particle size 63-20 µm was used as the samples for investigation considering the lower limit of ore dressing process which is tens to 100 µm. Rhamnolipid and sodium alginate as biosurfactant and aluminum sulfate which are mainly used as flocculant were used as environmentally friendly additives. Samples were adjusted to 2% liquid with deionized water then mixed with various concentrations of additives. The mixture was stirred with a magnetic bar during specific reaction times and then the liquid phase was separated by a centrifugal separator (Thermo Fisher Scientific, USA) under 4,000 rpm for 1 h. The separated liquid was filtered with a syringe and acrylic-based filter (0.45 µm). The extracted heavy metals in the filtered liquid were then determined using a UV-Vis spectrometer (DR-5000, Hach, USA) and a heat block (DBR 200, Hach, USA) followed by US EPA methods (8506, 8009, 10217 and 10220). Polymetallic nodule was mainly composed of manganese (27%), iron (8%), nickel (1.4%), cupper (1.3 %), cobalt (1.3%) and molybdenum (0.04%). Based on remediation standards of various countries, Nickel (Ni), Copper (Cu), Cadmium (Cd) and Zinc (Zn) were selected as primary target materials. Throughout this research, the use of rhamnolipid was shown to be an effective approach for removing heavy metals in samples originated from manganese nodules. Sodium alginate might also be one of the effective additives for the remediation of deep-sea mining tailings such as polymetallic nodules. Compare to the use of rhamnolipid and sodium alginate, aluminum sulfate was more effective additive at short reaction time within 4 h. Based on these results, sequencing particle separation, selective extraction/washing, advanced filtration of liquid phase, water treatment without dewatering and solidification/stabilization may be considered as candidate technologies for the remediation of deep-sea mining tailings.

Keywords: deep-sea mining tailings, heavy metals, remediation, extraction, additives

Procedia PDF Downloads 157

Authors: Tugrul Oktay, Mehmet Konar, Mustafa Soylak, Firat Sal, Murat Onay, Orhan Kizilkaya

Abstract:

In this paper, autonomous performance of a small manufactured unmanned helicopter is tried to be increased. For this purpose, a small unmanned helicopter is manufactured in Erciyes University, Faculty of Aeronautics and Astronautics. It is called as ZANKA-Heli-I. For performance maximization, autopilot parameters are determined via minimizing a cost function consisting of flight performance parameters such as settling time, rise time, overshoot during trajectory tracking. For this purpose, a stochastic optimization method named as simultaneous perturbation stochastic approximation is benefited. Using this approach, considerable autonomous performance increase (around %23) is obtained.

Keywords: small helicopters, hierarchical control, stochastic optimization, autonomous performance maximization, autopilots

Procedia PDF Downloads 582

Authors: Amjaad Alsalamah, Liyakathunsia Syed

Abstract:

Transportation is an essential need for many people to go to their work, school, and home. In particular, the main common method inside many cities is to drive the car. Driving a car can be an easy job to reach the destination and load all stuff in a reasonable time. However, deciding to find a parking lot for a car can take a long time using the traditional system that can issue a paper ticket for each customer. The old system cannot guarantee a parking lot for all customers. Also, payment methods are not always available, and many customers struggled to find their car among a numerous number of cars. As a result, this research focuses on providing an online smart parking system in order to save time and budget. This system provides a flexible management system for both parking owner and customers by receiving all request via the online system and it gets an accurate result for all available parking and its location.

Keywords: smart parking system, IoT, tracking system, process model, cost, time

Procedia PDF Downloads 337

Authors: Dileep Maarisetty, Janaki Komandur, Saroj S. Baral

Abstract:

In the current work, photocatalytic degradation of phenol was carried both in UV and visible light to find the slowest step that is limiting the rate of photo-degradation process. Characterization such as XRD, SEM, FT-IR, TEM, XPS, UV-DRS, PL, BET, UPS, ESR and zeta potential experiments were conducted to assess the credibility of catalysts in boosting the photocatalytic activity. To explore the synergy, TiO₂ was doped with graphene and alumina. The orbital hybridization with alumina doping (mediated by graphene) resulted in higher electron transfer from the conduction band of TiO₂ to alumina surface where oxygen reduction reactions (ORR) occur. Besides, the doping of alumina and graphene introduced defects into Ti lattice and helped in improving the adsorptive properties of modified photo-catalyst. Results showed that these defects promoted the oxygen reduction reactions (ORR) on the catalyst’s surface. ORR activity aims at producing reactive oxygen species (ROS). These ROS species oxidizes the phenol molecules which is adsorbed on the surface of photo-catalysts, thereby driving the photocatalytic reactions. Since mass transfer is considered as rate limiting step, various mathematical models were applied to the experimental data to probe the best fit. By varying the parameters, it was found that intra-particle diffusion was the slowest step in the degradation process. Lagergren model gave the best R² values indicating the nature of rate kinetics. Similarly, different adsorption isotherms were employed and realized that Langmuir isotherm suits the best with tremendous increase in uptake capacity (mg/g) of TiO₂-rGO-Al₂O₃ as compared undoped TiO₂. This further assisted in higher adsorption of phenol molecules. The results obtained from experimental, kinetic modelling and adsorption isotherms; it is concluded that apart from changes in surface, optoelectronic and morphological properties that enhanced the photocatalytic activity, the intra-particle diffusion within the catalyst’s pores serve as rate-limiting step in deciding the fate of photo-catalytic degradation of phenol.

Keywords: ORR, phenol degradation, photo-catalyst, rate kinetics

Procedia PDF Downloads 144

Authors: Hsueh-Hsing Lu, Thi-Cuc Le, Tung-Sheng Tsai, Chuen-Jinn Tsai

Abstract:

This study designed and tested a novel wet electrostatic precipitators (WEP) system featuring a Pulse-Air-Jet-Assisted Water Flow (PJWF) to shorten water cleaning time, reduce water usage, and maintain high particle removal efficiency. The PJWF injected cleaning water tangentially at the cylinder wall, rapidly enhancing the momentum of the water flow for efficient dust cake removal. Each PJWF cycle uses approximately 4.8 liters of cleaning water in 18 seconds. Comprehensive laboratory tests were conducted using a single-tube WEP prototype within a flow rate range of 3.0 to 6.0 cubic meters per minute(CMM), operating voltages between -35 to -55 kV, and high-frequency power supply. The prototype, consisting of 72 sets of double-spike rigid discharge electrodes, demonstrated that with the PJWF, -35 kV, and 3.0 CMM, the PM2.5 collection efficiency remained as high as the initial value of 88.02±0.92% after loading with Al2O3 particles at 35.75± 2.54 mg/Nm3 for 20-hr continuous operation. In contrast, without the PJWF, the PM2.5 collection efficiency drastically dropped from 87.4% to 53.5%. Theoretical modeling closely matched experimental results, confirming the robustness of the system's design and its scalability for larger industrial applications. Future research will focus on optimizing the PJWF system, exploring its performance with various particulate matter, and ensuring long-term operational stability and reliability under diverse environmental conditions. Recently, this WEP was combined with a preceding CT (cooling tower) and a HWS (honeycomb wet scrubber) and pilot-tested (40 CMM) to remove SO2 and PM2.5 emissions in a sintering plant of an integrated steel making plant. Pilot-test results showed that the removal efficiencies for SO2 and PM2.5 emissions are as high as 99.7 and 99.3 %, respectively, with ultralow emitted concentrations of 0.3 ppm and 0.07 mg/m3, respectively, while the white smoke is also eliminated at the same time. These new technologies are being used in the industry and the application in different fields is expected to be expanded to reduce air pollutant emissions substantially for a better ambient air quality.

Keywords: wet electrostatic precipitator, pulse-air-jet-assisted water flow, particle removal efficiency, air pollution control

Procedia PDF Downloads 25

Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

Abstract:

Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

Procedia PDF Downloads 373

Authors: Mohammad M. Khan, Gajendra Dixit

Abstract:

Partially lubricated sliding wear behaviour of a zinc-based alloy reinforced with 10wt% SiC particles has been studied as a function of applied load and solid lubricant particle size and has been compared with that of matrix alloy and conventionally used grey cast iron. The wear tests were conducted at the sliding velocities of 2.1m/sec in various partial lubricated conditions using pin on disc machine as per ASTM G-99-05. Base oil (SAE 20W-40) or mixture of the base oil with 5wt% graphite of particle sizes (7-10 µm) and (100 µm) were used for creating lubricated conditions. The matrix alloy revealed primary dendrites of a and eutectoid a + h and Î phases in the Inter dendritic regions. Similar microstructure has been depicted by the composite with an additional presence of the dispersoid SiC particles. In the case of cast iron, flakes of graphite were observed in the matrix; the latter comprised of (majority of) pearlite and (limited quantity of) ferrite. Results show a large improvement in wear resistance of the zinc-based alloy after reinforcement with SiC particles. The cast iron shows intermediate response between the matrix alloy and composite. The solid lubrication improved the wear resistance and friction behaviour of both the reinforced and base alloy. Moreover, minimum wear rate is obtained in oil+ 5wt % graphite (7-10 µm) lubricated environment for the matrix alloy and composite while for cast iron addition of solid lubricant increases the wear rate and minimum wear rate is obtained in case of oil lubricated environment. The cast iron experienced higher frictional heating than the matrix alloy and composite in all the cases especially at higher load condition. As far as friction coefficient is concerned, a mixed trend of behaviour was noted. The wear rate and frictional heating increased with load while friction coefficient was affected in an opposite manner. Test duration influenced the frictional heating and friction coefficient of the samples in a mixed manner.

Keywords: solid lubricant, sliding wear, grey cast iron, zinc based metal matrix composites

Procedia PDF Downloads 317

Authors: R. O’Reilly Meehan, D. B. Murray

Abstract:

In many practical situations, bubbles are dispersed in a liquid phase. Understanding these complex bubbly flows is therefore a key issue for applications such as shell and tube heat exchangers, mineral flotation and oxidation in water treatment. Although a large body of work exists for bubbles rising in an unbounded medium, that of bubbles rising in constricted geometries has received less attention. The particular case of a bubble sliding underneath an inclined surface is common to two-phase flow systems. The current study intends to expand this knowledge by performing experiments to quantify the streamwise flow structures associated with a single sliding air bubble under an inclined surface in quiescent water. This is achieved by means of two-dimensional, two-component particle image velocimetry (PIV), performed with a continuous wave laser and high-speed camera. PIV vorticity fields obtained in a plane perpendicular to the sliding surface show that there is significant bulk fluid motion away from the surface. The associated momentum of the bubble means that this wake motion persists for a significant time before viscous dissipation. The magnitude and direction of the flow structures in the streamwise measurement plane are found to depend on the point on its path through which the bubble enters the plane. This entry point, represented by a phase angle, affects the nature and strength of the vortical structures. This study reconstructs the vorticity field in the wake of the bubble, converting the field at different instances in time to slices of a large-scale wake structure. This is, in essence, Taylor’s ”frozen turbulence” hypothesis. Applying this to the vorticity fields provides a pseudo three-dimensional representation from 2-D data, allowing for a more intuitive understanding of the bubble wake. This study provides insights into the complex dynamics of a situation common to many engineering applications, particularly shell and tube heat exchangers in the nucleate boiling regime.

Keywords: bubbly flow, particle image velocimetry, two-phase flow, wake structures

Procedia PDF Downloads 378

Authors: Ali Kadir, S. R. Mishra, M. Shamshuddin, O. Anwar Beg

Abstract:

Motivation- Rotating disk bio-reactors are fundamental to numerous medical/biochemical engineering processes including oxygen transfer, chromatography, purification and swirl-assisted pumping. The modern upsurge in biologically-enhanced engineering devices has embraced new phenomena including bioconvection of micro-organisms (photo-tactic, oxy-tactic, gyrotactic etc). The proven thermal performance superiority of nanofluids i.e. base fluids doped with engineered nanoparticles has also stimulated immense implementation in biomedical designs. Motivated by these emerging applications, we present a numerical thermofluid dynamic simulation of the transport phenomena in bioconvection nanofluid rotating disk bioreactor flow. Methodology- We study analytically and computationally the time-dependent three-dimensional viscous gyrotactic bioconvection in swirling nanofluid flow from a rotating disk configuration. The disk is also deformable i.e. able to extend (stretch) in the radial direction. Stefan blowing is included. The Buongiorno dilute nanofluid model is adopted wherein Brownian motion and thermophoresis are the dominant nanoscale effects. The primitive conservation equations for mass, radial, tangential and axial momentum, heat (energy), nanoparticle concentration and micro-organism density function are formulated in a cylindrical polar coordinate system with appropriate wall and free stream boundary conditions. A mass convective condition is also incorporated at the disk surface. Forced convection is considered i.e. buoyancy forces are neglected. This highly nonlinear, strongly coupled system of unsteady partial differential equations is normalized with the classical Von Karman and other transformations to render the boundary value problem (BVP) into an ordinary differential system which is solved with the efficient Adomian decomposition method (ADM). Validation with earlier Runge-Kutta shooting computations in the literature is also conducted. Extensive computations are presented (with the aid of MATLAB symbolic software) for radial and circumferential velocity components, temperature, nanoparticle concentration, micro-organism density number and gradients of these functions at the disk surface (radial local skin friction, local circumferential skin friction, Local Nusselt number, Local Sherwood number, motile microorganism mass transfer rate). Main Findings- Increasing radial stretching parameter decreases radial velocity and radial skin friction, reduces azimuthal velocity and skin friction, decreases local Nusselt number and motile micro-organism mass wall flux whereas it increases nano-particle local Sherwood number. Disk deceleration accelerates the radial flow, damps the azimuthal flow, decreases temperatures and thermal boundary layer thickness, depletes the nano-particle concentration magnitudes (and associated nano-particle species boundary layer thickness) and furthermore decreases the micro-organism density number and gyrotactic micro-organism species boundary layer thickness. Increasing Stefan blowing accelerates the radial flow and azimuthal (circumferential flow), elevates temperatures of the nanofluid, boosts nano-particle concentration (volume fraction) and gyrotactic micro-organism density number magnitudes whereas suction generates the reverse effects. Increasing suction effect reduces radial skin friction and azimuthal skin friction, local Nusselt number, and motile micro-organism wall mass flux whereas it enhances the nano-particle species local Sherwood number. Conclusions - Important transport characteristics are identified of relevance to real bioreactor nanotechnological systems not discussed in previous works. ADM is shown to achieve very rapid convergence and highly accurate solutions and shows excellent promise in simulating swirling multi-physical nano-bioconvection fluid dynamics problems. Furthermore, it provides an excellent complement to more general commercial computational fluid dynamics simulations.

Keywords: bio-nanofluids, rotating disk bioreactors, Von Karman swirling flow, numerical solutions

Procedia PDF Downloads 157

Authors: Z. Bouchama, N. Essounbouli, A. Hamzaoui, M. N. Harmas

Abstract:

A new robust finite time synergetic controller is presented based on recently developed synergetic control methodology and a terminal attractor technique. A Fast Terminal Synergetic Control (FTSC) is proposed for controlling DC-DC buck converter. Unlike Synergetic Control (SC) and sliding mode control, the proposed control scheme has the characteristics of finite time convergence and chattering free phenomena. Simulation of stabilization and reference tracking for buck converter systems illustrates the approach effectiveness while stability is assured in the Lyapunov sense and converse Lyapunov results involving scalar differential inequalities are given for finite-time stability.

Keywords: dc-dc buck converter, synergetic control, finite time convergence, terminal synergetic control, fast terminal synergetic control, Lyapunov

Procedia PDF Downloads 462

Authors: Seyed Moslemi S. A. , Hesari J., Valizadeh H., Rezaiee-Mokaram R.

Abstract:

Nanotechnology and nanoscience and related fields in this area, will impact on daily human life in the not too distant future. The basic materials of liposomes are lipids. Lipids that can be used to build liposomes can be provided from variety of sources. In this research, lecithin and cholesterol were used to prepare liposomes. Probe sonicator was used to minimize the particles of liposome and make nanoliposomes. Encapsulation efficiency were analyzed with pyrogallol red indicator and autoanalizer equipment. The smallest particle size was 220 nanometer( 100 mg lecithin, 50 mg cholestrol, 12 min and amplitude of 90%). The highest encapsulation efficiency was 13.5%( 120 mg lecithin,45 mg cholestrol, 12 min and ampilitude of 92%).

Keywords: optimizing, nanoliposome, nisin, cheese

Procedia PDF Downloads 483

Authors: Tim Farrelly

Abstract:

In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

Procedia PDF Downloads 149

Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

Abstract:

Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

Procedia PDF Downloads 366

Authors: Agatha Bebbington, Terry Tetley, Kathryn Hadler

Abstract:

Background: Astronauts will set foot on the Moon later this decade, and are at high risk of lunar dust inhalation. Freshly-fractured lunar dust produces reactive oxygen species in solution, which are known to cause cellular damage and inflammation. Cytotoxicity and inflammatory mediator release was measured in pulmonary alveolar epithelial cells (cells that line the gas-exchange zone of the lung) exposed to a lunar dust simulant, LMS-1. It was hypothesised that freshly-fractured LMS-1 would result in increased cytotoxicity and inflammatory mediator release, owing to the angular morphology and high reactivity of fractured particles. Methods: A human alveolar epithelial type 1-like cell line (TT1) and a human macrophage-like cell line (THP-1) were exposed to 0-200μg/ml of unground, aged-ground, and freshly-ground LMS-1 (screened at <22μm). Cell viability, cytotoxicity, and inflammatory mediator release (IL-6, IL-8) were assessed using MMT, LDH, and ELISA assays, respectively. LMS-1 particles were characterised for their size, surface area, and morphology before and after grinding. Results: Exposure to LMS-1 particles did not result in overt cytotoxicity in either TT1 epithelial cells or THP-1 macrophage-like cells. A dose-dependent increase in IL-8 release was observed in TT1 cells, whereas THP-1 cell exposure, even at low particle concentrations, resulted in increased IL-8 release. Both cytotoxic and pro-inflammatory responses were most marked and significantly greater in TT1 and THP-1 cells exposed to freshly-fractured LMS-1. Discussion: LMS-1 is a novel lunar dust simulant; this is the first study to determine its toxicological effects on respiratory cells in vitro. An increased inflammatory response in TT1 and THP-1 cells exposed to ground LMS-1 suggests that low particle size, increased surface area, and angularity likely contribute to toxicity. Conclusions: Evenlow levels of exposure to LMS-1 could result in alveolar inflammation. This may have pathological consequences for astronauts exposed to lunar dust on future long-duration missions. Future research should test the effect of low-dose, intermittent lunar dust exposure on the respiratory system.

Keywords: lunar dust, LMS-1, lunar dust simulant, long-duration space travel, lunar dust toxicity

Procedia PDF Downloads 215

Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

Abstract:

Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

Procedia PDF Downloads 156

Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

Abstract:

There is a growing interest on the synthesis and characterization of nanoalloys since the unique chemical, and physical properties of nanoalloys can be tuned and, consequently, new structural motifs can be created by varying the type of constituent elements, atomic and magnetic ordering, as well as size and shape of the nanoparticles. Due to the fine size effects, magnetic nanoalloys have considerable attention with their enhanced mechanical, electrical, optical and magnetic behavior. As an important magnetic nanoalloy, the novel application area of Fe-Ni based nanoalloys is expected to be widened in the chemical, aerospace industry and magnetic biomedical applications. Noble metals have been using in biomedical applications for several years because of their surface plasmon properties. In this respect, iron-nickel nanoalloys are promising materials for magnetic biomedical applications because they show novel properties such as superparamagnetism and surface plasmon resonance property. Also, there is great attention for the usage Fe-Ni based nanoalloys as radar absorbing materials in aerospace and stealth industry due to having high Curie temperature, high permeability and high saturation magnetization with good thermal stability. In this study, FeNi₃ bimetallic nanoalloys were synthesized by mechanical alloying in a planetary high energy ball mill. In mechanical alloying, micron size powders are placed into the mill with milling media. The powders are repeatedly deformed, fractured and alloyed by high energy collision under the impact of balls until the desired composition and particle size is achieved. The experimental studies were carried out in two parts. Firstly, dry mechanical alloying with high energy dry planetary ball milling was applied to obtain FeNi₃ nanoparticles. Secondly, dry milling was followed by surfactant-assisted ball milling to observe the surfactant and solvent effect on the structure, size, and properties of the FeNi₃ nanoalloys. In the first part, the powder sample of iron-nickel was prepared according to the 1:3 iron to nickel ratio to produce FeNi₃ nanoparticles and the 1:10 powder to ball weight ratio. To avoid oxidation during milling, the vials had been filled with Ar inert gas before milling started. The powders were milled for 80 hours in total and the synthesis of the FeNi₃ intermetallic nanoparticles was succeeded by mechanical alloying in 40 hours. Also, regarding the particle size, it was found that the amount of nano-sized particles raised with increasing milling time. In the second part of the study, dry milling of the Fe and Ni powders with the same stoichiometric ratio was repeated. Then, to prevent agglomeration and to obtain smaller sized nanoparticles with superparamagnetic behavior, surfactants and solvent are added to the system, after 40-hour milling time, with the completion of the mechanical alloying. During surfactant-assisted ball milling, heptane was used as milling medium, and as surfactants, oleic acid and oleylamine were used in the high energy ball milling processes. The characterization of the alloyed particles in terms of microstructure, morphology, particle size, thermal and magnetic properties with respect to milling time was done by X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, vibrating-sample magnetometer, and differential scanning calorimetry.

Keywords: iron-nickel systems, magnetic nanoalloys, mechanical alloying, nanoalloy characterization, surfactant-assisted ball milling

Procedia PDF Downloads 180

Authors: Jamboor K. Vishwanatha

Abstract:

Among the potent anti-cancer agents, curcumin has been found to be very efficacious against various cancer cells. Despite multiple medicinal benefits of curcumin, poor water solubility, poor physiochemical properties and low bioavailability continue to pose major challenges in developing a formulation for clinical efficacy. To improve its potential application in the clinical area, we formulated poly lactic-co-glycolic acid (PLGA) nanoparticles. The PLGA nanoparticles were formulated using solid-oil/water emulsion solvent evaporation method and then characterized for percent yield, encapsulation efficiency, surface morphology, particle size, drug distribution within nanoparticles and drug polymer interaction. Our studies showed the successful formation of smooth and spherical curcumin loaded PLGA nanoparticles with a high percent yield of about 92.01±0.13% and an encapsulation efficiency of 90.88±0.14%. The mean particle size of the nanoparticles was found to be 145nm. The in vitro drug release profile showed 55-60% drug release from the nanoparticles over a period of 24 hours with continued sustained release over a period of 8 days. Exposure to curcumin loaded nanoparticles resulted in reduced cell viability of cancer cells compared to normal cells. We used a novel non-covalent insertion of a homo-bifunctional spacer for targeted delivery of curcumin to various cancer cells. Functionalized nanoparticles for antibody/targeting agent conjugation was prepared using a cross-linking ligand, bis(sulfosuccinimidyl) suberate (BS3), which has reactive carboxyl group to conjugate efficiently to the primary amino groups of the targeting agents. In our studies, we demonstrated successful conjugation of antibodies, Annexin A2 or prostate specific membrane antigen (PSMA), to curcumin loaded PLGA nanoparticles for targeting to prostate and breast cancer cells. The percent antibody attachment to PLGA nanoparticles was found to be 92.8%. Efficient intra-cellular uptake of the targeted nanoparticles was observed in the cancer cells. These results have emphasized the potential of our multifunctional curcumin nanoparticles to improve the clinical efficacy of curcumin therapy in patients with cancer.

Keywords: polymeric nanoparticles, cancer therapy, sustained release, curcumin

Procedia PDF Downloads 325

Authors: Sun Lim, Kyun Jung

Abstract:

In this paper, we describe the control strategy of high speed parallel robot system with EtherCAT network. This work deals the parallel robot system with centralized control on the real-time operating system such as window TwinCAT3. Most control scheme and algorithm is implemented master platform on the PC, the input and output interface is ported on the slave side. The data is transferred by maximum 20usecond with 1000byte. EtherCAT is very high speed and stable industrial network. The control strategy with EtherCAT is very useful and robust on Ethernet network environment. The developed parallel robot is controlled pre-design nonlinear controller for 6G/0.43 cycle time of pick and place motion tracking. The experiment shows the good design and validation of the controller.

Keywords: parallel robot control, etherCAT, nonlinear control, parallel robot inverse kinematic

Procedia PDF Downloads 571

Authors: Anna Cameron, Chunxia Zhao, Haofei Wang, Yun Liu, Guang Ze Yang

Abstract:

Since the first publication in 1775, cancer research has built a comprehensive understanding of how cellular components of the tumor niche promote disease development. However, only within the last decade has research begun to establish the impact of non-cellular components of the niche, particularly the extracellular matrix (ECM). The ECM, a three-dimensional scaffold that sustains the tumor microenvironment, plays a crucial role in disease progression. Cancer cells actively deregulate and remodel the ECM to establish a tumor-promoting environment. Recent work has highlighted the need to further our understanding of the complexity of this cancer-ECM relationship. In vitro models use hydrogels to mimic the ECM, as hydrogel matrices offer biological compatibility and stability needed for long term cell culture. However, natural hydrogels are being used in these models verbatim, without tuning their biophysical characteristics to achieve pathophysiological relevance, thus limiting their broad use within cancer research. The biophysical attributes of these gels dictate cancer cell proliferation, invasion, metastasis, and therapeutic response. Evaluating the three most widely used natural hydrogels, Matrigel, collagen, and agarose gel, the permeability, stiffness, and pore-size of each gel were measured and compared to the in vivo environment. The pore size of all three gels fell between 0.5-6 µm, which coincides with the 0.1-5 µm in vivo pore size found in the literature. However, the stiffness for hydrogels able to support cell culture ranged between 0.05 and 0.3 kPa, which falls outside the range of 0.3-20,000 kPa reported in the literature for an in vivo ECM. Permeability was ~100x greater than in vivo measurements, due in large part to the lack of cellular components which impede permeation. Though, these measurements prove important when assessing therapeutic particle delivery, as the ECM permeability decreased with increasing particle size, with 100 nm particles exhibiting a fifth of the permeability of 10 nm particles. This work explores ways of adjusting the biophysical characteristics of hydrogels by changing protein concentration and the trade-off, which occurs due to the interdependence of these factors. The global aim of this work is to produce a more pathophysiologically relevant model for each tumor type.

Keywords: cancer, extracellular matrix, hydrogel, microfluidic

Procedia PDF Downloads 92

Authors: Massoud Farag Abouklaish

Abstract:

The main aim of the present study is to investigate and classify the particle size distribution of sandy soils in Libya. More than fifty soil samples collected from many regions in North, West and South of Libya. Laboratory sieve analysis tests performed on disturbed soil samples to determine grain size distribution. As well as to provide an indicator of general engineering behavior and good understanding, test results are presented and analysed. In addition, conclusions, recommendations are made.

Keywords: Libya, grain size, sandy soils, sieve analysis tests

Procedia PDF Downloads 615

Authors: Ndumbe Eric Esongami, Manga Veronica Ebot, Foba Josepha Tendo, Yengong Fabrice Lamfu, Tiku David Tambe

Abstract:

The prevalence and unpleasant nature of plastics pollution constantly observed on beach shore on stormy events has prompt researchers worldwide to thesis on sustainable economic and environmental designs on plastics, especially in Cameroon, a major touristic destination in the Central Africa Region. The inconsistent protocols develop by researchers has added to this burden, thus the morphological nature of microplastic remediation is a call for concerns. The prime aim of the study is to morphologically identify, quantify and forensically understands the distribution of each plastics polymer composition. Duplicates of 2×2 m (4m2) quadrants were sampled in each beach/month over 8 months period across five purposive beaches along the Limbe – Idenau coastline, Cameroon. Collected plastic samples were thoroughly washed and separation done using a 2 mm sieve. Only particles of size, < 2 mm, were considered and forward follow the microplastics laboratory analytical processes. Established step by step methodological procedures of particle filtration, organic matter digestion, density separation, particle extraction and polymer identification including microscope and were applied for the beach microplastics samples. Microplastics were observed in each sample/beach/month with an overall abundance of 241 particles/number weighs 89.15 g in total and with a mean abundance of 2 particles/m2 (0.69 g/m2) and 6 particles/month (2.0 g/m2). The accumulation of beach shoreline MPs rose dramatically towards decreasing size with microbeads and fiber only found in the < 1 mm size fraction. Approximately 75% of beach MPs contamination were found in LDB 2, LDB 1 and IDN beaches/average particles/number while the most dominant polymer type frequently observed also were PP, PE, and PS in all morphologically parameters analysed. Beach MPs accumulation significantly varied temporally and spatially at p = 0.05. ANOVA and Spearman’s rank correlation used shows linear relationships between the sizes categories considered in this study. In terms of polymer MPs analysis, the colour class recorded that white coloured MPs was dominant, 50 particles/number (22.25 g) with recorded abundance/number in PP (25), PE (15) and PS (5). The shape class also revealed that irregularly shaped MPs was dominant, 98 particles/number (30.5 g) with higher abundance/number in PP (39), PE (33), and PS (11). Similarly, MPs type class shows that fragmented MPs type was also dominant, 80 particles/number (25.25 g) with higher abundance/number in PP (30), PE (28) and PS (15). Equally, the sized class forward revealed that 1.5 – 1.99 mm sized ranged MPs had the highest abundance of 102 particles/number (51.77 g) with higher concentration observed in PP (47), PE (41), and PS (7) as well and finally, the weight class also show that 0.01 g weighs MPs was dominated by 98 particles/number (56.57 g) with varied numeric abundance seen in PP (49), PE (29) and PS (13). The forensic investigation of the pollution indicated that majority of the beach microplastic is sourced from the site/nearby area. The investigation could draw useful conclusions regarding the pathways of pollution. The fragmented microplastic, a significant component in the sample, was found to be sourced from recreational activities and partly from fishing boat installations and repairs activities carried out close to the shore.

Keywords: forensic analysis, beach MPs, particle/number, polymer composition, cameroon

Procedia PDF Downloads 79

Authors: Jonjaua Ranogajec, Ognjen Rudic, Snezana Pasalic, Snezana Vucetic, Damir Cjepa

Abstract:

The paper involves a chain of activities from synthesis, establishment of the methodology for characterization and testing of novel protective materials through the pilot production and application on model supports. It summarizes the results regarding the development of the pilot production protocol for newly developed self-cleaning materials. The optimization of the production parameters was completed in order to improve the most important functional properties (mineralogy characteristics, particle size, self-cleaning properties and photocatalytic activity) of the newly designed nanocomposite material.

Keywords: pilot production, self-cleaning materials, compatibility, cultural heritage

Procedia PDF Downloads 395

Authors: Charles Kwasi Antwi, Mohammad Naushad Emmambux, Natalia Rosa-Sibakov

Abstract:

The consumption of high-fibre snacks is beneficial in reducing the prevalence of most non-communicable diseases and improving human health. However, using high-fibre flour to produce snacks by extrusion cooking reduces the expansion ratio of snacks, thereby decreasing sensory properties and consumer acceptability of the snack. The study determines the effects of adding Viscozyme®-treated sorghum bran on the properties of extruded sorghum snacks with the aim of producing high-fibre expanded snacks with acceptable quality. With a twin-screw extruder, sorghum endosperm flour [by decortication] with and without sorghum bran and with enzyme-treated sorghum bran was extruded at high shear rates with feed moisture of 20%, feed rate of 10 kg/hr, screw speed of 500 rpm, and temperature zones of 60°C, 70°C, 80°C, 140°C, and 140°C toward the die. The expanded snacks that resulted from this process were analysed in terms of their physical (expansion ratio, bulk density, colour profile), chemical (soluble and insoluble dietary fibre), and functional (water solubility index (WSI) and water absorption index (WAI)) characteristics. The expanded snacks produced from refined sorghum flour enriched with Viscozyme-treated bran had similar expansion ratios to refined sorghum flour extrudates, which were higher than those for untreated bran-sorghum extrudate. Sorghum extrudates without bran showed higher values of expansion ratio and low values of bulk density compared to the untreated bran extrudates. The enzyme-treated fibre increased the expansion ratio significantly with low bulk density values compared to untreated bran. Compared to untreated bran extrudates, WSI values in enzyme-treated samples increased, while WAI values decreased. Enzyme treatment of bran reduced particle size and increased soluble dietary fibre to increase expansion. Lower particle size suggests less interference with bubble formation at the die. Viscozyme-treated bran-sorghum composite flour could be used as raw material to produce high-fibre expanded snacks with improved physicochemical and functional properties.

Keywords: extrusion, sorghum bran, decortication, expanded snacks

Procedia PDF Downloads 93

Authors: Maria Grazia Albanesi, Riccardo Amadeo

Abstract:

This study presents a new model of the human image quality assessment process: the aim is to highlight the foundations of the image quality metrics proposed in literature, by identifying the cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to create a novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effective objective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biases are not taken in account at all. We then propose a possible methodology to address this issue.

Keywords: eye-tracking, image quality assessment metric, MOS, quality of user experience, visual perception

Procedia PDF Downloads 413

Authors: Maha Jazouli

Abstract:

Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

Procedia PDF Downloads 190

Authors: Sandra Baßler, Peter Dünow, Mathias Marquardt

Abstract:

A Fourier series based learning control (FSBLC) algorithm for tracking trajectories of mechanical systems with unknown nonlinearities is presented. Two processes are introduced to which the FSBLC with PD controller is applied. One is a simplified service robot capable of climbing stairs due to special wheels and the other is a propeller driven pendulum with nearly the same requirements on control. Additionally to the investigation of learning the feed forward for the desired trajectories some considerations on the implementation of such an algorithm on low cost microcontroller hardware are made. Simulations of the service robot as well as practical experiments on the pendulum show the capability of the used FSBLC algorithm to perform the task of improving control behavior for repetitive task of such mechanical systems.

Keywords: climbing stairs, FSBLC, ILC, service robot

Procedia PDF Downloads 315

Authors: Ambika Selvaraj

Abstract:

Magnetic iron oxide nanoparticles (IO) of < 20nm (superparamagnetic) become promising tool in cancer therapy, and integrated nanodevices for cancer detection and screening. The obstacles include particle heterogeneity and cost. It can be overcome by developing monodispersed nanoparticles in economical approach. We have successfully synthesized < 7 nm IO by low temperature controlled technique, in which Fe0 is sandwiched between stabilizer and Fe2+. Size analysis showed the excellent size control from 31 nm at 33°C to 6.8 nm at 10°C. Resultant monodispersed IO were found to be stable for > 50 reuses, proved its applicability in biomedical applications.

Keywords: low temperature synthesis, hybrid iron nanoparticles, cancer therapy, biomedical applications

Procedia PDF Downloads 344

Authors: Amr Emam, Joseph Victor, Mohamed Abd Elghany

Abstract:

The paper presents the effect of the orbit inclination on the pointing error of the satellite antenna and consequently on its footprint on earth for a typical Ku- band payload system. The performance assessment is examined both theoretically and by means of practical measurements, taking also into account all additional sources of pointing errors, such as East-West station keeping, orbit eccentricity and actual attitude control performance. An implementation and computation of the sinusoidal biases in satellite roll and pitch used to compensate the pointing error of the satellite antenna coverage is studied and evaluated before and after the pointing corrections performed. A method for evaluation of the performance of the implemented biases has been introduced through measuring satellite received level from a tracking 11m and fixed 4.8m transmitting antenna before and after the implementation of the pointing corrections.

Keywords: satellite, inclined orbit, pointing errors, coverage optimization

Procedia PDF Downloads 405

Authors: R. Burahee, B. Chassinat, T. de Laclos, A. Dépée, A. Sastim

Abstract:

The purpose of this paper is to propose a solution to detect, predict and reconstitute rain drops in real time – during the night – using an embedded material with an infrared camera. To prevent the system from needing too high hardware resources, simple models are considered in a powerful image treatment algorithm reducing considerably calculation time in OpenCV software. Using a smart model – drops will be matched thanks to a process running through two consecutive pictures for implementing a sophisticated tracking system. With this system drops computed trajectory gives information for predicting their future location. Thanks to this technique, treatment part can be reduced. The hardware system composed by a Raspberry Pi is optimized to host efficiently this code for real time execution.

Keywords: reconstitution, prediction, detection, rain drop, real time, raspberry, infrared

Procedia PDF Downloads 420

Authors: Soheila Sadeghi

Abstract:

Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

Procedia PDF Downloads 61