Search results for: morphology optimization

Authors: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

Procedia PDF Downloads 141

Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

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The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

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Authors: Mardin Abdalqadir, Paul Adzakro, Tannaz Pak, Sina Rezaei Gomari

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Climate change and global warming recently became significant concerns due to the massive emissions of greenhouse gases into the atmosphere, predominantly CO2 gases. Therefore, it is necessary to find sustainable and inexpensive methods to capture the greenhouse gasses and protect the environment for live species. The application of naturally available and cheap adsorbents of carbon such as clay minerals became a great interest. However, the minerals prone to low storage capacity despite their high affinity to adsorb carbon. This paper aims to explore ways to improve the pore volume and surface area of two selected clay minerals, ‘montmorillonite and kaolinite’ by acid treatment to overcome their low storage capacity. Montmorillonite and kaolinite samples were treated with different sulfuric acid concentrations (0.5, 1.2 and 2.5 M) at 40 °C for 8 hours to achieve the above aim. The grain size distribution and morphology of clay minerals before and after acid treatment were explored with Scanning Electron Microscope to evaluate surface area improvement. The ImageJ software was used to find the porosity and pore volume of treated and untreated clay samples. The structure of the clay minerals was also analyzed using an X-ray Diffraction machine. The results showed that the pore volume and surface area were increased substantially through acid treatment, which speeded up the rate of carbon dioxide adsorption. XRD pattern of kaolinite did not change after sulfuric acid treatment, which indicates that acid treatment would not affect the structure of kaolinite. It was also discovered that kaolinite had a higher pore volume and porosity than montmorillonite before and after acid treatment. For example, the pore volume of untreated kaolinite was equal to 30.498 um3 with a porosity of 23.49%. Raising the concentration of acid from 0.5 M to 2.5 M in 8 hours’ time reaction led to increased pore volume from 30.498 um3 to 34.73 um3. The pore volume of raw montmorillonite was equal to 15.610 um3 with a porosity of 12.7%. When the acid concentration was raised from 0.5 M to 2.5 M for the same reaction time, pore volume also increased from 15.610 um3 to 20.538 um3. However, montmorillonite had a higher specific surface area than kaolinite. This study concludes that clay minerals are inexpensive and available material sources to model the realistic conditions and apply the results of carbon capture to prevent global warming, which is one of the most critical and urgent problems in the world.

Keywords: acid treatment, kaolinite, montmorillonite, pore volume, porosity, surface area

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Authors: Mohammed Elsayed Lotfy Elsayed Abouzeid, Tomonobu Senjyu

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A novel multi-objective park and ride control approach is presented in this research. Park and ride will encourage the owners of the vehicles to leave their cars in the nearest points (on the edges of the crowded cities) and use public transportation facilities (train, bus, metro, or mon-rail) to reach their work inside the crowded city. The proposed control scheme is used to design electric vehicle charging stations (EVCS) to charge 1000 electric vehicles (EV) during their owners' work time. Cairo, Egypt is used as a case study. Photovoltaic (PV) and battery energy storage system (BESS) are used to meet the EVCS demand. Two multi-objective optimization techniques (MOGA and epsilon-MOGA) are utilized to get the optimal sizes of PV and BESS so as to meet the load demand and minimize the total life cycle cost. Detailed analysis and comparison are held to investigate the performance of the proposed control scheme using MATLAB.

Keywords: Battery Energy Storage System, Electric Vehicle, Park and Ride, Photovoltaic, Multi-objective

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Authors: Violeta Damjanovic-Behrendt

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This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

Keywords: security, internet of things, cloud computing, stackelberg game, machine learning, naive q-learning

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Authors: Taufik Rizkiandi, Teuku Yuri M. Zagloel, Andri Dwi Setiawan

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Distribution and growth in the transportation and warehousing business sector decreased by 15,04%. There was a decrease in Gross Domestic Product (GDP) contribution level from rank 7 of 4,41% in 2019 to 3,81% in rank 8 in 2020. A decline in the transportation and warehousing business sector contributes to GDP, resulting in oil and gas companies implementing an efficient supply chain strategy to ensure the availability of goods, especially lubricants. Fluctuating demand for lubricants and warehouse service time limits are essential things that are taken into account in determining an efficient route. Add depots points as a solution so that demand for lubricants is fulfilled (not stock out). However, adding a depot will increase operating costs and storage costs. Therefore, it is necessary to optimize the addition of depots using the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). This research case study was conducted at an oil and gas company that produces lubricants from 2019 to 2021. The study results obtained the optimal route and the addition of a depot with a minimum additional cost. The total cost remains efficient with the addition of a depot when compared to one depot from Jakarta.

Keywords: CVRPTW, optimal route, depot, tabu search algorithm

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Authors: Doaa H. Elgohary, Dina M. Hamoda, S. Yahia

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Technical textiles refer to textile materials that are engineered and designed to have specific functionalities and performance characteristics beyond their traditional use as apparel or upholstery fabrics. These textiles are usually developed for their unique properties such as strength, durability, flame retardancy, chemical resistance, waterproofing, insulation and other special properties. The development and use of technical textiles are constantly evolving, driven by advances in materials science, manufacturing technologies and the demand for innovative solutions in various industries. Kevlar 29 is a type of aramid fiber developed by DuPont. It is a high-performance material known for its exceptional strength and resistance to impact, abrasion, and heat. Kevlar 29 belongs to the Kevlar family, which includes different types of aramid fibers. Kevlar 29 is primarily used in applications that require strength and durability, such as ballistic protection, body armor, and body armor for military and law enforcement personnel. It is also used in the aerospace and automotive industries to reinforce composite materials, as well as in various industrial applications. Two different Kevlar samples were used coated with cooper lithium silicate (CLS); ten different mechanical and physical properties (weight, thickness, tensile strength, elongation, stiffness, air permeability, puncture resistance, thermal conductivity, stiffness, and spray test) were conducted to approve its functional performance efficiency. The influence of different mechanical properties was statistically analyzed using an independent t-test with a significant difference at P-value = 0.05. The radar plot was calculated and evaluated to determine the best-performing samples. The results of the independent t-test observed that all variables were significantly affected by yarn counts except water permeability, which has no significant effect. All properties were evaluated for samples 1 and 2, a radar chart was used to determine the best attitude for samples. The radar chart area was calculated, which shows that sample 1 recorded the best performance, followed by sample 2. The surface morphology of all samples and the coating materials was determined using a scanning electron microscope (SEM), also Fourier Transform Infrared Spectroscopy Measurement for the two samples.

Keywords: cooper lithium silicate, independent t-test, kevlar, technical textiles.

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Authors: Gamze Karanfil Celep, Kevser Dincer

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The effects of polymer concentration and electrospinning process parameters on the average diameters of electrospun polyacrylonitrile (PAN) nanofibers were experimentally investigated. Besides, mechanical and thermal properties of PAN nanofibers were examined by tensile test and thermogravimetric analysis (TGA), respectively. For this purpose, the polymer concentration, solution feed rate, supply voltage and tip-to-collector distance were determined as the control factors. To succeed these aims, Taguchi’s L16 orthogonal design (4 parameters, 4 level) was employed for the experimental design. Optimal electrospinning conditions were defined using the signal-to-noise (S/N) ratio that was calculated from diameters of the electrospun PAN nanofibers according to "the-smaller-the-better" approachment. In addition, analysis of variance (ANOVA) was evaluated to conclude the statistical significance of the process parameters. The smallest diameter of PAN nanofibers was observed. According to the S/N ratio response results, the most effective parameter on finding out of nanofiber diameter was determined. Finally, the Taguchi design of experiments method has been found to be an effective method to statistically optimize the critical electrospinning parameters used in nanofiber production. After determining the optimum process parameters of nanofiber production, electrical conductivity and fuel cell performance of electrospun PAN nanofibers on the carbon papers will be evaluated.

Keywords: nanofiber, electrospinning, polyacrylonitrile, Taguchi method

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Authors: Seyyed Masoud Seyyedoshohadaei, Borhanuddin Mohd Ali

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To support group mobility, the NEMO Basic Support Protocol has been standardized as an extension of Mobile IP that enables an entire network to change its point of attachment to the Internet. Using NEMO in IEEE 802.16e (WiMax) networks causes latency in handover procedure and affects seamless communication of real-time applications. To decrease handover latency and service disruption time, an integrated scheme named Optimized Fast NEMO (OFNEMO) was introduced by authors of this paper. In OFNEMO a pre-establish multi tunnels concept, cross function optimization and cross layer design are used. In this paper, an analytical model is developed to evaluate total cost consisting of signaling and packet delivery costs of the OFNEMO compared with RFC3963. Results show that OFNEMO increases probability of predictive mode compared with RFC3963 due to smaller handover latency. Even though OFNEMO needs extra signalling to pre-establish multi tunnel, it has less total cost thanks to its optimized algorithm. OFNEMO can minimize handover latency for supporting real time application in moving networks.

Keywords: fast mobile IPv6, handover latency, IEEE802.16e, network mobility

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Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Hussein M. Etmimi, Peter E. Mallon

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Electrospinning uses an electrical charge to draw very fine fibers (typically on the micro or nano scale) from a liquid or molten precursor. Over the years, this method has become a widely used and a successful technique to process polymer materials and their composites into nanofibers. The main focus of this work is to study the electrospinning of multi-phase amphiphilic copolymers and their nanocomposites, which contain graphene as the nanofiller material. In such amphiphilic materials, the constituents segments are incompatible and thus the solid state morphology will be determined by the composition of the various constituents as well as the method of preparation. In this study, amphiphilic block copolymers of poly(dimethyl siloxane) and poly(methyl methacrylate) (PDMS-b-PMMA) with well-defined structures were synthesized and the solution electrospinning of these materials and their properties were investigated. Atom transfer radical polymerization (ATRP) was used to obtain the controlled block copolymers with relatively high molar masses and narrow dispersity. First, PDMS macroinitiators with different chain length of 1000, 5000 and 10000 g/mol were synthesized by the reaction of monocarbinol terminated PDMS with α-bromoisobutyryl bromide initiator. The obtained macroinitiators were used for the polymerization of methyl methacrylate monomer to obtain the desired block copolymers using the ATRP process. Graphene oxide (GO) of different loading was then added to the copolymer solution and the resultant nanocomposites were successfully electrospun into nanofibers. The electrospinning was achieved using dimethylformamide/chloroform mixture (60:40 vl%) as electrospinning solution medium. Scanning electron microscopy (SEM) showed the successful formation of the electrospun fibers with dimensions in the nanometer range. X-ray diffraction indicated that the GO nanosheets were of an exfoliated structure, irrespective of the filler loading. Thermogravimetric analysis also showed that the thermal stability of the nanofibers was improved in the presence of GO, which was not a function of the filler loading. Differential scanning calorimetry also showed that the mechanical properties (measured as glass transition temperature) of the nanofibers was improved significantly in the presence of GO, which was a function of the filler loading.

Keywords: elctrospinning, graphene oxide, nanofibers, polymethyl methacrylate (PMMA)

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Authors: Mohammadreza Heydariazad

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Productivity growth of wind energy as a clean source needed to achieve improved strategy in production and transmission and management of wind resources in order to increase quality of power and reduce costs. New technologies based on power converters that cause changing turbine speed to suit the wind speed blowing turbine improve extraction efficiency power from wind. This article introduces variable speed wind turbines and optimization of power, and presented methods to use superconducting inductor in the composition of power converter and is proposed the dc measurement for the wind farm and especially is considered techniques available to them. In fact, this article reviews mechanisms and function, changes of wind speed turbine according to speed control strategies of various types of wind turbines and examines power possible transmission and ac from producing location to suitable location for a strong connection integrating wind farm generators, without additional cost or equipment. It also covers main objectives of the dynamic control of wind turbines, and the methods of exploitation and the ways of using it that includes the unique process of these components. Effective algorithm is presented for power control in order to extract maximum active power and maintains power factor at the desired value.

Keywords: wind energy, generator, superconducting inductor, wind turbine power

Procedia PDF Downloads 328

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Ajay Kumar Choubey, Geeta Agnihotri, C. Sasikumar, Rashmi Dwivedi

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Deep-drawing operations are performed widely in industrial applications. It is very important for efficiency to achieve parts with no or minimum defects. Deep drawn parts are used in high performance, high strength and high reliability applications where tension, stress, load and human safety are critical considerations. Wrinkling is a kind of defect caused by stresses in the flange part of the blank during metal forming operations. To avoid wrinkling appropriate blank-holder pressure/force or drawbead can be applied. Now-a-day computer simulation plays a vital role in the field of manufacturing process. So computer simulation of manufacturing has much advantage over previous conventional process i.e. mass production, good quality of product, fast working etc. In this study, a two dimensional elasto-plastic Finite Element (F.E.) model for Mild Steel material blank has been developed to study the behavior of the flange wrinkling and deep drawing parameters under different Blank-Holder Pressure (B.H.P.). For this, commercially available Finite Element software ANSYS 14 has been used in this study. Simulation results are critically studied and salient conclusions have been drawn.

Keywords: ANSYS, deep drawing, BHP, finite element simulation, wrinkling

Procedia PDF Downloads 450

Authors: Halison da Silva Pereira, Ciro Sobrinho Campolina Martins, Vitor Mainenti Leal Lopes

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Long range performance is a goal for aircraft configuration optimization. Blended Wing Body (BWB) is presented in many works of literature as the most aerodynamically efficient design for a fixed-wing aircraft. Because of its high weight to thrust ratio, BWB is the ideal configuration for many Unmanned Aerial Vehicle (UAV) missions on geomatics applications. In this work, a BWB aerodynamic design for typical light geomatics payload is presented. Aerodynamic non-dimensional coefficients are predicted using low Reynolds number computational techniques (3D Panel Method) and wing parameters like aspect ratio, taper ratio, wing twist and sweep are optimized for high cruise performance and flight quality. The methodology of this work is a summary of tailless aircraft wing design and its application, with appropriate computational schemes, to light UAV subjected to low Reynolds number flows leads to conclusions like the higher performance and flight quality of thicker airfoils in the airframe body and the benefits of using aerodynamic twist rather than just geometric.

Keywords: blended wing body, low Reynolds number, panel method, UAV

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Chi-Chang Lin, Jian-Rong Wu, Jiun-Yan Chiu

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Myopia, ubiquitous symptom that is necessary to correct the eyesight by optical lens struggles many people for their daily life. Recent years, younger people raise interesting on using contact lens because of its convenience and aesthetics. In clinical, the risk of eye infections increases owing to the behavior of incorrectly using contact lens unsupervised cleaning which raising the infection risk of cornea, named ocular keratitis. In order to overcome the identification needs, new detection or analysis method with rapid and more accurate identification for clinical microorganism is importantly needed. In our study, we take advantage of Raman spectroscopy having unique fingerprint for different functional groups as the distinct and fast examination tool on microorganism. As we know, Raman scatting signals are normally too weak for the detection, especially in biological field. Here, we applied special SERS enhancement substrates to generate higher Raman signals. SERS filter we designed in this article that prepared by deposition of silver nanoparticles directly onto cellulose filter surface and suspension nanoparticles - gold nanostars (AuNSs) also be introduced together to achieve better enhancement for lower concentration analyte (i.e., various bacteria). Research targets also focusing on studying the shape effect of synthetic AuNSs, needle-like surface morphology may possible creates more hot-spot for getting higher SERS enhance ability. We utilized new designed SERS technology to distinguish the bacteria from ocular keratitis under strain level, and specific Raman and SERS fingerprint were grouped under pattern recognition process. We reported a new method combined different SERS substrates can be applied for clinical microorganism detection under strain level with simple, rapid preparation and low cost. Our presenting SERS technology not only shows the great potential for clinical bacteria detection but also can be used for environmental pollution and food safety analysis.

Keywords: bacteria, gold nanostars, Raman spectroscopy surface-enhanced Raman scattering filter

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Authors: D. S. Naumann, B. J. Evans, O. Hassan

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This paper outlines the development of an automated aerodynamic optimisation algorithm using a novel method of parameterising a computational mesh by employing user–defined control nodes. The shape boundary movement is coupled to the movement of the novel concept of the control nodes via a quasi-1D-linear deformation. Additionally, a second order smoothing step has been integrated to act on the boundary during the mesh movement based on the change in its second derivative. This allows for both linear and non-linear shape transformations dependent on the preference of the user. The domain mesh movement is then coupled to the shape boundary movement via a Delaunay graph mapping. A Modified Cuckoo Search (MCS) algorithm is used for optimisation within the prescribed design space defined by the allowed range of control node displacement. A finite volume compressible NavierStokes solver is used for aerodynamic modelling to predict aerodynamic design fitness. The resulting coupled algorithm is applied to a range of test cases in two dimensions including the design of a subsonic, transonic and supersonic intake and the optimisation approach is compared with more conventional optimisation strategies. Ultimately, the algorithm is tested on a three dimensional wing optimisation case.

Keywords: mesh movement, aerodynamic shape optimization, cuckoo search, shape parameterisation

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: Ahmed Ibrahim Galadima, Abdullahi Muhammed Bello, Abdullateef Akintunde Raji, Ruqayyah Mujahidah Abdullateef, Hajara Sani Labaran

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Sesamum indicium is an erect, herbaceous, branched, and warm-season annual crop. It differs in growth habit, form and shape, seed size and color, composition, size, and color of flowers. The experiments were performed by collecting two accessions of Sesamum indicum (white and black varieties). The morphological parameters like plant height and leaf size were measured using a ruler, while stem girth was observed using a vernier caliper. Germinability assessments were conducted by placing 100 seeds from each of the two sesame varieties and presoaked in 5 per cent sodium hypochlorite for 15 min., followed by rinse with distilled water. Germinability was assessed by placing the seeds in moist conditions and analyzing the outcome accordingly. The results from the experiments showed that the plant height (41.98 cm), stem girth (3.23 cm), and size of leaves (13.89 cm2) were higher in the white sesame variety when compared to the sesame black variety where 34.30 cm, 2.68 cm, and 7.47 cm2, respectively were obtained. But, from the black sesame variety, the number of leaves and the number of branches high values (105.06 cm) and (10.41), respectively were discovered. And significant differences were recorded in all the analyzed morphological parameters between the two sesame accessions, except stem girth. More so, the white variety of the sesame plant has demonstrated a good reproductive capability with the number of flowers (7.18), number of capsules (17.44), 100 seeds weight (1.67 g), and 1000 seeds weight (16.67 g). However, none of the analyzed reproductive parameters was observed from the black sesame variety. The white sesame variety was observed to have a higher number of Trichomes per microscopic view by almost 7 folds when compared to the black variety. But, improved size of stomata was detected in the black sesame variety by over 1.5 folds compared to the white variety. The germinability analysis had shown that from the sesame white variety, 98 seeds out of the 100 seeds sown were able to germinate, which signifies 98 percent germinability. Whereas 86 seeds out of the 100 seeds sown have germinated in petri dishes from the black sesame variety, which suggests 86 per cent germinability. Therefore, this research obviously showed that the white sesame variety displayed remarkable morphological qualities and, accordingly could be employed for farming purposes.

Keywords: accessions of sesame plant, characterization, growth, morphology

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Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif

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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.

Keywords: beamforming, interference, mutual information, wireless communications

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Authors: Felix Boehnisch, Alexander Lutz

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Based on the number of users and the amount of content posted daily, Facebook is considered the largest social network in the world. This content includes images or text posts from companies but also private persons, which are also commented on by other users. However, it can sometimes be difficult for companies to keep track of all the posts and the reactions to them, especially when there are several posts a day that contain hundreds to thousands of comments. To facilitate this, the following paper deals with the possible applications of sentiment analysis to social media comments in order to be able to support the work in social media marketing. In a first step, post comments were divided into positive and negative by a subjective rating, then the same comments were checked for their polarity value by the two german python libraries TextBlobDE and SentiWS and also grouped into positive, negative, or even neutral. As a control, the subjective classifications were compared with the machine-generated ones by a confusion matrix, and relevant quality criteria were determined. The accuracy of both libraries was not really meaningful, with 60% to 66%. However, many words or sentences were not evaluated at all, so there seems to be room for optimization to possibly get more accurate results. In future studies, the use of these specific German libraries can be optimized to gain better insights by either applying them to stricter cleaned data or by adding a sentiment value to emojis, which have been removed from the comments in advance, as they are not contained in the libraries.

Keywords: Facebook, German libraries, polarity, sentiment analysis, social media comments

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: Rutuja Upadhyay, Anurag Mehra

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Solid food foams/cellular foods are colloidal systems which impart structure, texture and mouthfeel to many food products such as bread, cakes, ice-cream, meringues, etc. Their heterogeneous morphology makes the quantification of structure/mechanical relationships complex. The porous structure of solid food foams is highly influenced by the processing conditions, ingredient composition, and their interactions. Sensory perceptions of food foams are dependent on bubble size, shape, orientation, quantity and distribution and determines the texture of foamed foods. The state and structure of the solid matrix control the deformation behavior of the food, such as elasticity/plasticity or fracture, which in turn has an effect on the force-deformation curves. The obvious step in obtaining the relationship between the mechanical properties and the porous structure is to quantify them simultaneously. Here, we attempt to research food foams such as bread dough, baked bread and steamed rice cakes to determine the link between ingredients and the corresponding effect of each of them on the rheology, microstructure, bubble size and texture of the final product. Dynamic rheometry (SAOS), confocal laser scanning microscopy, flatbed scanning, image analysis and texture profile analysis (TPA) has been used to characterize the foods studied. In all the above systems, there was a common observation that when the mean bubble diameter is smaller, the product becomes harder as evidenced by the increase in storage and loss modulus (G′, G″), whereas when the mean bubble diameter is large the product is softer with decrease in moduli values (G′, G″). Also, the bubble size distribution affects texture of foods. It was found that bread doughs with hydrocolloids (xanthan gum, alginate) aid a more uniform bubble size distribution. Bread baking experiments were done to study the rheological changes and mechanisms involved in the structural transition of dough to crumb. Steamed rice cakes with xanthan gum (XG) addition at 0.1% concentration resulted in lower hardness with a narrower pore size distribution and larger mean pore diameter. Thus, control of bubble size could be an important parameter defining final food texture.

Keywords: food foams, rheology, microstructure, texture

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Authors: Celestine Mbakaan, Iorkyaa Ahemen, A. D. Onoja, A. N. Amah, Emmanuel Barki

Abstract:

Rice husk (RH) is a natural sheath that forms and covers the grain of rice. The husk composed of hard materials, including opaline silica and lignin. It separates from its grain during rice milling. RH also contains approximately 15 to 28 wt % of silica in hydrated amorphous form. Nanosilica was derived from the husk of different rice varieties after pre-treating the husk (RH) with HCl and calcination at 550°C. Nanosilica derived from the husk of Osi rice variety produced the highest silica yield, and further pretreatment with 0.8 M H₃PO₄ acid removed more mineral impurities. The silica obtained from this rice variety was selected as a host matrix for doping with Sm³⁺ ions. Rice husk silica (RH-SiO₂) doped with samarium (RH-SiO₂: xSm³⁺ (x=0.01, 0.05, and 0.1 molar ratios) nanophosphors were synthesized via the sol-gel method. The structural analysis by X-ray diffraction analysis (XRD) reveals amorphous structure while the surface morphology, as revealed by SEM and TEM, indicates agglomerates of nano-sized spherical particles with an average particle size measuring 21 nm. The nanophosphor has a large surface area measuring 198.0 m²/g, and Fourier transform infrared spectroscopy (FT-IR) shows only a single absorption band which is strong and broad with a valley at 1063 cm⁻¹. Diffuse reflectance spectroscopy (DRS) shows strong absorptions at 319, 345, 362, 375, 401, and 474 nm, which can be exclusively assigned to the 6H5/2→4F11/2, 3H7/2, 4F9/2, 4D5/2, 4K11/2, and 4M15/2 + 4I11/2, transitions of Sm³⁺ respectively. The photoluminescence excitation spectra show that near UV and blue LEDs can effectively be used as excitation sources to produce red-orange and yellow-orange emission from Sm³⁺ ion-doped RH-SiO₂ nanophosphors. The photoluminescence (PL) of the nanophosphors gives three main lines; 568, 605, and 652 nm, which are attributed to the intra-4f shell transitions from the excited level to ground levels, respectively under excitation wavelengths of 365 and 400 nm. The result, as confirmed from the 1931 CIE coordinates diagram, indicates the emission of red-orange light by RH-SiO₂: xSm³⁺ (x=0.01 and 0.1 molar ratios) and yellow-orange light from RH-SiO₂: 0.05 Sm³⁺. Finally, the result shows that RH-SiO₂ doped with samarium (Sm³⁺) ions can be applicable in display applications.

Keywords: luminescence, nanosilica, nanophosphors, Sm³⁺

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

Abstract:

This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: Srinivas Vangari

Abstract:

With the technological advancements around the globe, artificial intelligence (AI) has boosted supply chain management (SCM) by improving efficiency, sensitivity, and promptness. Artificial intelligence-based SCM provides comprehensive perceptions of consumer behavior in dynamic market situations and trends, foreseeing the accurate demand. It reduces overproduction and stockouts while optimizing production planning and streamlining operations. Consequently, the AI-driven SCM produces a customer-centric supply with resilient and robust operations. Intending to delve into the transformative significance of AI in SCM, this study focuses on improving efficiency in SCM with the integration of AI, understanding the production demand, accurate forecasting, and particular production planning. The study employs a mixed-method approach and expert survey insights to explore the challenges and benefits of AI applications in SCM. Further, a case analysis is incorporated to identify the best practices and potential challenges with the critical success features in AI-driven SCM. Key findings of the study indicate the significant advantages of the AI-integrated SCM, including optimized inventory management, improved transportation and logistics management, cost optimization, and advanced decision-making, positioning AI as a pivotal force in the future of supply chain management.

Keywords: artificial intelligence, supply chain management, accurate forecast, accurate planning of production, understanding demand

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Authors: Mojtaba Esmaeilzad Limoudehi, Ebrahim Amiri

Abstract:

Water scarcity is now one of the leading challenges for human societies. In this regard, recognizing the relationship between soil, water, plant growth, and plant response to stress is very significant. In this paper, considering the importance of drought stress and the role of choosing suitable cultivars in resistance against drought, a split-plot experiment using early, intermediate, and late-maturing cultivars was carried out in Katul filed, Golestan province during two cultivation years of 2015 and 2016. The main factor was irrigation intervals at four levels, including 7 days, 14 days, 21 days, and 28 days. The subfactor was the subplot of six maize cultivars (two early maturing cultivars, two medium maturing cultivars, and two late-maturing cultivars). The results of variance analysis have revealed that irrigation interval and cultivars treatment have significant effects on the number of grain in each corn, number of rows in each corn, number of grain per row, the weight of 1000 grains, grain yield, and biomass yield. Although, the interaction of these two factors on the mentioned attributes was meaningful. The best grain yield was achieved at 7 days irrigation interval and late maturing maize cultivars treatment, which was equal to 12301 kg/ha.

Keywords: corn, growth period, optimization, stress

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Authors: Debasish Das, Mainak Mitra, A.Chaudhuri

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For the purpose of producing moisture vapor permeable waterproof cotton fabric to be used for protective apparel against rain, cotton fabric was coated with the blend of natural rubber and chloroprene rubber containing ammonium acetate as the water-soluble salt, employing a calendar coating technique. Rubber formulations also contained filler, homogenizer, and a typical sulphur curing system. Natural rubber and chloroprene blend in the blend ratio of 30: 70, containing 25 parts of sodium acetate per hundred parts of rubber was coated on the fabric. The coated fabric was vulcanized thereafter at 140oC for 3 h. Coated and vulcanized fabric was subsequently dipped in water for 45 min, followed by drying in air. Such set of treatments produced optimum results. Coated, vulcanized, washed and dried cotton fabric showed optimum developments in the property profiles in respect of waterproofness, breathability as revealed by moisture vapor transmission rate, coating adhesion, tensile properties, abrasion resistance, flex endurance and fire retardancy. Incorporation of highly water-soluble ammonium acetate salt in the coating formulation and their subsequent removal from vulcanized coated layer affected by post washing in consequent to dipping in the water-bath produced holes of only a few microns in the coating matrix of the fabric. Such microporous membrane formed on the cotton fabric allowed only transportation of moisture vapor through them, giving a moisture vapor transmission rate of 3734 g/m2/24h, while acting as a barrier for large liquid water droplet resisting 120cm of the water column in the hydrostatic water-head tester, rendering the coated cotton fabric waterproof. Examination of surface morphology of vulcanized coating by scanning electron microscopy supported the mechanism proposed for development of breathable waterproof layer on cotton fabric by the process employed above. Such process provides an easy and cost-effective route for achieving moisture vapor permeable waterproof cotton.

Keywords: moisture vapour permeability, waterproofness, chloroprene, calendar coating, coating adhesion, fire retardancy

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Authors: Mitesh Rathod, Jungho Ahn, Noo Li Jeon, Junghoon Lee

Abstract:

Endothelial cells respond to cues from both biochemical as well as micro mechanical environment. Significant effort has been directed to understand the effects of biochemical signaling, however, relatively little is known about regulation of endothelial cell biology by the micro mechanical environment. Numerous studies have been performed to understand how physical forces regulate endothelial cell behavior. In this regard, past studies have majorly focused on exploring how fluid shear stress governs endothelial cell behavior. Parallel plate flow chambers and rectangular microchannels are routinely employed for applying fluid shear force on endothelial cells. However, these studies fall short in mimicking the in vivo like micro environment from topological aspects. Few studies have only used circular microchannels to replicate in vivo like condition. Seldom efforts have been directed to elucidate the combined effect of topology, substrate rigidity and fluid shear stress on endothelial cell response. In this regard, we demonstrate a facile fabrication process to develop a hybrid polydimethylsiloxane microfluidic platform to study endothelial cell biology. On a single chip microchannels with different cross sections i.e., circular, rectangular and square have been fabricated. In addition, our fabrication approach allows variation in the substrate rigidity along the channel length. Two different variants of polydimethylsiloxane, namely Sylgard 184 and Sylgard 527, were utilized to achieve the variation in rigidity. Moreover, our approach also enables in creating Y bifurcation circular microchannels. Our microfluidic platform thus facilitates for conducting studies pertaining to endothelial cell morphology with respect to change in topology, substrate rigidity and fluid flow on a single chip. The hybrid platform was tested by culturing Human Umbilical Vein Endothelial Cells in circular microchannels with varying substrate rigidity, and exposed to fluid shear stress of 12 dynes/cm² and static conditions. Results indicate the cell area response to flow induced shear stress was governed by the underlying substrate mechanics.

Keywords: hybrid, microfluidic platform, PDMS, shear flow, substrate rigidity

Procedia PDF Downloads 277