Search results for: aerospace applications

Authors: Kevlin Govender, Anthony Walker, Glen Bright

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Mass customization is an area of increased importance and the development of rapid tooling applications is pivotal to the success of mass customization. This paper presents a laminated object manufacturing (LOM) process for rapid tooling. The process is termed 3D metal laminate printing and utilizes domestic-grade aluminum foil and epoxy for layered manufacturing. A detailed explanation of the process is presented to produce complex metal laminated composite parts. Aluminum-epoxy composite specimens were manufactured from 0.016mm aluminum and subjected to tensile tests to determine the mechanical properties of the manufactured composite in relation to solid metal specimens. The fracture zone of the specimens was analyzed under scanning electron microscopy (SEM) in order to characterize the fracture mode and study the interfacial bonding of the manufactured laminate specimens.

Keywords: 3D metal laminate printer, aluminum-epoxy composite, laminated object manufacturing, rapid tooling

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Authors: Hamed Mohammadi Mofarah, Mutalifu Abulikemu, Ghassan E. Jabbour

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Personal protective equipment (PPE) is finding increasing interest in incorporating silver nanoparticles (NPs) for various applications including microbial disinfection and shielding against electromagnetic waves. In this venue, we present an in situ reactive coating approach where silver nanoparticles are self-assembled on the surface of cotton yarn. The impacts of a variety of experimental parameters on the average size of the synthesized silver NPs were investigated. These include vacuum conditions, the concentration of the silver salt solution and reducer, temperature, and curing time. Silver NPs with an average size ranging from 10 to 50 nanometers were self-assembled as a result of careful regulation of such reaction conditions. The disinfection efficacy against the COVID surrogate virus of the functional textile reached a rate of 99.99%. On the other hand, the silver NPs decorated textile demonstrated an electromagnetic shielding ranging from 31 dB to 45 dB were achieved for the frequency range 8.2-12.4 GHz.

Keywords: antiviral, COVID, electromagnetic shielding, in-situ reactive coating, SARS CoV 2, silver nanoparticles, smart textile

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Authors: K. N. Kipreou, E. Efthmiadou, G. Kordas

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Biofouling represents one of the most crucial problems in the present maritime industries when its control still challenges the researchers all over the world. The present work is referred to the synthesis and characterization CeMo and Cu2O nanocontainers by using a wide range of techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermogravimetric analysis (TGA) for marine applications. The above nanosystems will be loaded with active monomers and corrosion rendering healing ability to marine paints. The objective of this project is their ability for self-healing, self-polishing and finally for anti-corrosion activity. One of the driving forces for the exploration of CeMo, is the unique anticorrosive behavior, which will be confirmed by the electrochemistry methodology. It has be highlighted that the nanocontainers of Cu2O with the appropriate antibacterial inhibitor will improve the hydrophobicity and the morphology of the coating surfaces reducing the water friction. In summary, both novel nanoc will increase the lifetime of the paints releasing the antifouling agent in a control manner.

Keywords: marinepaints, nanocontainer, antifouling, anticorrosion, copper, electrochemistry, coating, biofouling, inhibitors, copper oxide, coating, SEM

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Authors: Naima Guenifi, Shiromani Balmukund Rahi, Amina Bechka

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Tunnel FET is one of the most suitable alternatives FET devices for conventional CMOS technology for low-power electronics and applications. Due to its lower subthreshold swing (SS) value, it is a strong follower of low power applications. It is a quantum FET device that follows the band to band (B2B) tunneling transport phenomena of charge carriers. Due to band to band tunneling, tunnel FET is suffering from a lower switching current than conventional metal-oxide-semiconductor field-effect transistor (MOSFET). For improvement of device features and limitations, the newly invented negative capacitance concept of ferroelectric material is implemented in conventional Tunnel FET structure popularly known as NC TFET. The present research work has implemented the idea of high-k gate dielectric added with ferroelectric material on double gate Tunnel FET for implementation of negative capacitance. It has been observed that the idea of negative capacitance further improves device features like SS value. It helps to reduce power dissipation and switching energy. An extensive investigation for circularity uses for digital, analog/RF and linearity features of double gate NCTFET have been adopted here for research work. Several essential designs paraments for analog/RF and linearity parameters like transconductance(gm), transconductance generation factor (gm/IDS), its high-order derivatives (gm2, gm3), cut-off frequency (fT), gain-bandwidth product (GBW), transconductance generation factor (gm/IDS) has been investigated for low power RF applications. The VIP₂, VIP₃, IMD₃, IIP₃, distortion characteristics (HD2, HD3), 1-dB, the compression point, delay and power delay product performance have also been thoroughly studied.

Keywords: analog/digital, ferroelectric, linearity, negative capacitance, Tunnel FET, transconductance

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Authors: Yogita Patil-Sen

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Magnetic nanoparticles such as those made of iron oxide have been widely explored as biocatalysts, contrast agents, and drug delivery systems. However, some of the challenges associated with these particles are agglomeration and biocompatibility, which lead to concern of toxicity of the particles, especially for drug delivery applications. Coating the particles with biocompatible materials such as lipids and peptides have shown to improve the mentioned issues. Thus, these core-shell type nanoparticles are emerging as the new class of nanomaterials for targeted drug delivery applications. In this study, various types of core-shell magnetic nanoparticles are prepared and characterized using techniques, such as Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Vibrating Sample Magnetometer (VSM) and Thermogravimetric Analysis (TGA). The heating ability of nanoparticles is tested under oscillating magnetic field. The efficacy of the nanoparticles as drug carrier is also investigated. The loading of an anticancer drug, Doxorubicin at 18 °C is measured up to 48 hours using UV-visible spectrophotometer. The drug release profile is obtained under thermal incubation condition at 37 °C and compared with that under the influence of oscillating field. The results suggest that the core-shell nanoparticles exhibit superparamagnetic behaviour, although, coating reduces the magnetic properties of the particles. Both the uncoated and coated particles show good heating ability, again it is observed that coating decreases the heating behaviour of the particles. However, coated particles show higher drug loading efficiency than the uncoated particles and the drug release is much more controlled under the oscillating magnetic field. Thus, the results strongly indicate the suitability of the prepared core-shell type nanoparticles as drug delivery vehicles and their potential in magnetic hyperthermia applications and for hyperthermia cancer therapy.

Keywords: core-shell, hyperthermia, magnetic nanoparticles, targeted drug delivery

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Authors: Gloria P. Manu, Johnson K. Efavi, Abu Yaya, Grace K. Arkorful, Frank Godson

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Plastics have been used extensively in both food and water packaging and other applications because of their inherent properties of low bulk densities and inertness as well as its low cost. Waste management of these plastics after usage is troubling in Ghana. One way of addressing the environmental problems associated with these plastic wastes is by recycling into useful products such as composites for energy and construction applications using natural or local materials as reinforcement. In this work, composites have been formed from waste low-density polyethylene (LDPE) and kaolin at temperatures as low as 70 ֯C using low-cost solvents like kerosene. Chemical surface modifications have been employed to improve the interfacial bonding resulting in the enhancement of properties of the composites. Kaolin particles of sizes ≤ 90µm were dispersed in the polyethylene matrix. The content of the LDPE was varied between 10, 20, 30, 40, 50, 60, and 70 %wt. Results obtained indicated that all the composites exhibited impressive compressive and flexural strengths with the 50%wt. composition having the highest strength. The hardness value of the composites increased as the polyethylene composition reduces and that of the kaolin increased. The average density and water of absorption of the composites were 530kg/m³ and 1.3% respectively.

Keywords: polyethylene, recycling, waste, composite, kaolin

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Authors: Shaher Bano, Samia Fida, Asif Israr

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The continuous development and exploitation of materials and designs have diverted the attention of the world towards the use of robust composite materials known as fiber-metal laminates in many high-performance applications. The hybrid structure of fiber metal laminates makes them a material of choice for various applications such as aircraft skin panels, fuselage floorings, door panels and other load bearing applications. The synergistic effect of properties of metals and fibers reinforced laminates are responsible for their high damage tolerance as the metal element provides better fatigue and impact properties, while high stiffness and better corrosion properties are inherited from the fiber reinforced matrix systems. They are mostly used as a layered structure in different joint configurations such as lap and but joints. The FML layers are usually bonded with each other using either mechanical fasteners or adhesive bonds. This research work is also focused on modification of an adhesive bonded joint as a single lap joint of carbon fibers based CARALL FML has been modified to increase interlaminar shear strength and avoid delamination. For this purpose different joint modification techniques such as the introduction of spews and shoulder to modify the bond shape and use of nanofillers such as carbon nano-tubes as a reinforcement in the adhesive materials, have been utilized to improve shear strength of lap joint of the adhesively bonded FML layers. Both the simulation and experimental results showed that lap joint with spews and shoulders configuration have better properties due to stress distribution over a large area at the corner of the joint. The introduction of carbon nanotubes has also shown a positive effect on shear stress and joint strength as they act as reinforcement in the adhesive bond material.

Keywords: adhesive joint, Carbon Reinforced Aluminium Laminate (CARALL), fiber metal laminates, spews

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Authors: Amit Bhanushali

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In the ever-changing landscape of software development, automated software testing has emerged as a critical component of the Software Development Life Cycle (SDLC). This research undertakes a comparative study of three major automated testing tools -UFT, Selenium, and RPA- evaluating them on usability, maintenance, and effectiveness. Leveraging existing JAVA-based applications as test cases, the study aims to guide testers in selecting the optimal tool for specific applications. By exploring key features such as source and licensing, testing expenses, object repositories, usability, and language support, the research provides practical insights into UFT, Selenium, and RPA. Acknowledging the pivotal role of these tools in streamlining testing processes amid time constraints and resource limitations, the study assists professionals in making informed choices aligned with their organizational needs.

Keywords: software testing tools, software development lifecycle (SDLC), test automation frameworks, automated software, JAVA-based, UFT, selenium and RPA (robotic process automation), source and licensing, object repository

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Authors: Richard, Iyan Subiyanto, Chairul Hudaya

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Activated carbon has been playing a significant role for many applications, especially in energy storage devices. However, commercially activated carbons generally require complicated processes and high production costs. Therefore, in this study, an activated carbon originating from green coke waste, that is economically affordable will be used as a carbon source. To synthesize activated carbon, KOH as an activator was employed with variation of C:KOH in ratio of 1:2, 1:3, 1:4, and 1:5, respectively, with an activation temperature of 700°C. The characterizations of activated carbon are obtained from Scanning Electron Microscopy, Energy Dispersive X-Ray, Raman Spectroscopy, and Brunauer-Emmett-Teller. The optimal activated carbon sample with specific surface area of 2,024 m²/g with high carbon content ( > 80%) supported by the high porosity carbon image obtained by SEM was prepared at C:KOH ratio of 1:4. The result shows that the synthesized activated carbon would be an ideal choice for energy storage device applications. Therefore, this study is expected to reduce the costs of activated carbon production by expanding the utilization of petroleum waste.

Keywords: activated carbon, energy storage material, green coke, specific surface area

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Authors: Bashar Mudhaffar Abdullah, Hasniza Zaman Huri, Nany Hairunisa

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This study was carried out to determine the thermal properties and spectroscopy study of Malaysian Jatropha curcas seed oil. The J. curcas seed oil physicochemical properties such as free fatty acid (FFA %), acid value, saponification value, iodine value, unsaponifiable matter, and viscosity (cp) gave values of 1.89±0.10%, 3.76±0.07, 203.36±0.36 mg/g, 4.90±0.25, 1.76±0.03%, and 32, respectively. Gas chromatography (GC) was used to determine the fatty acids (FAs) composition. J. curcas seed oil is consisting of saturated FAs (19.55%) such as palmitic (13.19%), palmitoleic (0.40%), and stearic (6.36%) acids and unsaturated FAs (80.42%) such as oleic (43.32%) and linoleic (36.70%) acids. The thermal properties using differential scanning calorimetry (DSC) showed that crystallized TAG was observed at -6.79°C. The melting curves displayed three major exothermic regions of J. curcas seed oil, monounsaturated (lower-temperature peak) at -31.69°C, di-unsaturated (medium temperature peak) at -20.23°C and tri-unsaturated (higher temperature peak) at -12.72°C. The results of this study showed that the J. curcas seed oil is a plausible source of polyunsaturated fatty acid (PUFA) to be developed in the future for pharmaceutical applications.

Keywords: Jatropha curcas seed oil, thermal properties, crystallization, melting, spectroscopy

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Paul V. Thomas, Mostafa S. A. Elsayed, Denis Walch

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Airframe structural optimization at different design stages results in new mass and stiffness distributions which modify the critical design loads envelop. Determination of aircraft critical loads is an extensive analysis procedure which involves simulating the aircraft at thousands of load cases as defined in the certification requirements. It is computationally prohibitive to use a Global Finite Element Model (GFEM) for the load analysis, hence reduced order structural models are required which closely represent the dynamic characteristics of the GFEM. This paper presents the implementation of Component Mode Synthesis (CMS) method for the generation of high fidelity Reduced Order Model (ROM) of complex airframes. Here, sub-structuring technique is used to divide the complex higher order airframe dynamical system into a set of subsystems. Each subsystem is reduced to fewer degrees of freedom using matrix projection onto a carefully chosen reduced order basis subspace. The reduced structural matrices are assembled for all the subsystems through interface coupling and the dynamic response of the total system is solved. The CMS method is employed to develop the ROM of a Bombardier Aerospace business jet which is coupled with an aerodynamic model for dynamic aeroelasticity loads analysis under gust turbulence. Another set of dynamic aeroelastic loads is also generated employing a stick model of the same aircraft. Stick model is the reduced order modelling methodology commonly used in the aerospace industry based on stiffness generation by unitary loading application. The extracted aeroelastic loads from both models are compared against those generated employing the GFEM. Critical loads Modal participation factors and modal characteristics of the different ROMs are investigated and compared against those of the GFEM. Results obtained show that the ROM generated using Craig Bampton CMS reduction process has a superior dynamic characteristics compared to the stick model.

Keywords: component mode synthesis, craig bampton reduction method, dynamic aeroelasticity analysis, model order reduction

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

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Authors: Rohaya Abdul Wahab, Raja Mohd Fuad Tengku Aziz, Nazaliza Othman, Sharifah Saleh, Nabihah Razali, Rozaimah Baharim, M. Hanif M. Nasir

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This paper will discuss how EDA tools are integrated and automated in an Integrated Circuit Design Environment. Some of the problems face in our current environment is that users need to configure manually on the library paths, start-up files and project directories. Certain manual processes that happen between the users and applications can be automated but they must be transparent to the users. For example, the users can run the applications directly after login without knowing the library paths and start-up files locations. The solution to these problems is to automate the processes using standard configuration files which will benefit the users and EDA support. This paper will discuss how the implementation is done to automate the process using scripting languages such as Perl, Tcl, Scheme and Shell Script. These scripting tools are great assets for design engineers to build a robust and powerful design flow and this technique is widely used to integrate all the tools together.

Keywords: EDA tools, Integrated Circuits, scripting, integration, automation

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Authors: Georgeta Voicu, Cristina Daniela Ghitulica, Andreia Cucuruz, Cristina Busuioc

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In the field of tissue engineering, the compositional and microstructural features of the employed materials play an important role, with implications on the mechanical and biological behaviour of the medical devices. In this context, the development of apatite - natural biopolymer composites represents a choice of many scientific groups. Thus, hydroxyapatite powders were synthesized by a wet method, namely co-precipitation, starting from high purity reagents (CaO, MgO, and H3PO4). Moreover, the substitution of calcium with magnesium have been approached, in the 5 - 10 wt.% range. Afterward, the phosphate powders were integrated in two types of composites with chitosan, different from morphological point of view. First, 3D porous scaffolds were obtained by a freeze-drying procedure. Second, uniform, compact films were achieved by film casting. The influence of chitosan molecular weight (low, medium and high), as well as apatite powder to polymer ratio (1:1 and 1:2) on the morphological properties, were analysed in detail. In conclusion, the reported biocomposites, prepared by a straightforward route are suitable for bone substitution or repairing applications.

Keywords: bone reconstruction, chitosan, composite scaffolds, hydroxyapatite

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Authors: Jiří Kubásek, Peter Minárik, Klára Hosová, Stanislav Šašek, Jozef Veselý, Jitka Stráská, Drahomír Dvorský, Dalibor Vojtěch, Miloš Janeček

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Mg-2Y-2Gd-1Ca and Mg-4Y-4Gd-2Ca alloys were processed by extrusion or equal channel angular pressing (ECAP) to analyse the effect of the microstructure on ignition temperature, mechanical properties and corrosion resistance. The alloys are characterized by good mechanical properties and exceptionally high ignition temperature, which is a critical safety measure. The effect of extrusion and ECAP on the microstructure, mechanical properties and ignition temperature was studied. The obtained results indicated a substantial effect of the processing conditions on the average grain size, the recrystallized fraction and texture formation. Both alloys featured a high strength, depending on the composition and processing condition, and a high ignition temperature of ≈1100 °C (Mg-4Y-4Gd-2Ca) and ≈950 °C (Mg-2Y-2Gd-1Ca), which was attributed to the synergic effect of Y, Gd and Ca oxides, with the dominant effect of Y₂O₃. The achieved combination of enhanced mechanical properties and the ignition temperature makes these alloys a prominent candidate for aircraft applications.

Keywords: magnesium alloys, enhanced ignition temperature, mechanical properties, ECAP

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Authors: Karim Sobh, Khaled El-Ayat, Fady Morcos, Amr El-Kadi

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Distributed applications deployed on LEO satellites and ground stations require substantial communication between different members in a constellation to overcome the earth coverage barriers imposed by GEOs. Applications running on LEO constellations suffer the earth line-of-sight blockage effect. They need adequate lab testing before launching to space. We propose a scalable cloud-based net-work simulation framework to simulate problems created by the earth line-of-sight blockage. The framework utilized cloud IaaS virtual machines to simulate LEO satellites and ground stations distributed software. A factorial ANOVA statistical analysis is conducted to measure simulator overhead on overall communication performance. The results showed a very low simulator communication overhead. Consequently, the simulation framework is proposed as a candidate for testing LEO constellations with distributed software in the lab before space launch.

Keywords: LEO, cloud computing, constellation, satellite, network simulation, netfilter

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Maram Shahad Dana Anfal

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This research paper presents the design of a surveillance drone with computer-aided durability and model analyses that provides a cost-effective and efficient solution for various applications. The quadcopter's design is based on a lightweight and strong structure made of materials such as aluminum and titanium, which provide a durable structure for the quadcopter. The structure of this product and the computer-aided durability system are both designed to ensure frequent repairs or replacements, which will save time and money in the long run. Moreover, the study discusses the drone's ability to track, investigate, and deliver objects more quickly than traditional methods, makes it a highly efficient and cost-effective technology. In this paper, a comprehensive analysis of the quadcopter's operation dynamics and limitations is presented. In both simulation and experimental data, the computer-aided durability system and the drone's design demonstrate their effectiveness, highlighting the potential for a variety of applications, such as search and rescue missions, infrastructure monitoring, and agricultural operations. Also, the findings provide insights into possible areas for improvement in the design and operation of the drone. Ultimately, this paper presents a reliable and cost-effective solution for surveillance applications by designing a drone with computer-aided durability and modeling. With its potential to save time and money, increase reliability, and enhance safety, it is a promising technology for the future of surveillance drones. operation dynamic equations have been evaluated successfully for different flight conditions of a quadcopter. Also, CAE modeling techniques have been applied for the modal risk assessment at operating conditions.Stress analysis have been performed under the loadings of the worst-case combined motion flight conditions.

Keywords: drone, material, solidwork, hypermesh

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

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Authors: V. K. Banga

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Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic

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Authors: O. Mauroner, L. Le, S. Best

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Digital technologies offer many opportunities in the design and implementation of brand communication and advertising. Augmented reality (AR) is an innovative technology in marketing communication that focuses on the fact that virtual interaction with a product ad offers additional value to consumers. AR enables consumers to obtain (almost) real product experiences by the way of virtual information even before the purchase of a certain product. Aim of AR applications in relation with advertising is in-depth examination of product characteristics to enhance product knowledge as well as brand knowledge. Interactive design of advertising provides observers with an intense examination of a specific advertising message and therefore leads to better brand knowledge. The elaboration likelihood model and the central route to persuasion strongly support this argumentation. Nevertheless, AR in brand communication is still in an initial stage and therefore scientific findings about the impact of AR on information processing and brand attitude are rare. The aim of this paper is to empirically investigate the potential of AR applications in combination with traditional print advertising. To that effect an experimental design with different levels of interactivity is built to measure the impact of interactivity of an ad on different variables o advertising effectiveness.

Keywords: advertising effectiveness, augmented reality, brand communication, brand recall

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Authors: Sandesh Achar

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Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Asteria Nsamba

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Social networking applications and tools have become compelling platforms for generating and sharing knowledge across the world. Social networking applications and tools refer to a variety of social media platforms which include Facebook, Twitter WhatsApp, blogs and Wikis. The most popular of these platforms are Facebook, with 2.41 billion active users on a monthly basis, followed by WhatsApp with 1.6 billion users and Twitter with 330 million users. These communication platforms have not only impacted social lives but have also impacted students’ learning, across different delivery modes in higher education: distance, conventional and blended learning modes. With this amount of interest in these platforms, knowledge sharing has gained importance within the context in which it is required. In open distance learning (ODL) contexts, social networking platforms can offer students and teachers the platform on which to create and share knowledge, and form learning collaborations. Thus, they can serve as support mechanisms to increase interactions and reduce isolation and loneliness inherent in ODL. Despite this potential and opportunity, research indicates that many ODL teachers are not inclined to using social media tools in learning. Although it is unclear why these tools are uncommon in these environments, concerns raised in the literature have indicated that many teachers have not mastered the art of teaching with technology. Using technological, pedagogical content knowledge (TPCK) and product quality theory, and Bloom’s Taxonomy as lenses, this paper is aimed at; firstly, assessing the quality of three social media applications: Facebook, Twitter and WhatsApp, in order to determine the extent to which they are suitable platforms for teaching and learning, in terms of content generation, information sharing and learning collaborations. Secondly, the paper demonstrates the application of teaching, learning and assessment using Bloom’s Taxonomy.

Keywords: distance education, quality, social networking tools, TPACK

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Authors: Alireza Rafieerad, Bushroa Abd Razak, Bahman Nasiri Tabrizi, Jamunarani Vadivelu

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Recently, reports on the fabrication of nanotubular arrays have generated considerable scientific interest, owing to the broad range of applications of the oxide nanotubes in solar cells, orthopedic and dental implants, photocatalytic devices as well as lithium-ion batteries. A more attractive approach for the fabrication of oxide nanotubes with controllable morphology is the electrochemical anodization of substrate in a fluoride-containing electrolyte. Consequently, titanium dioxide nanotubes (TiO2 NTs) have been highly considered as an applicable material particularly in the district of artificial implants. In addition, regarding long-term efficacy and reasons of failing and infection after surgery of currently used dental implants required to enhance the cytocompatibility properties of Ti-based bone-like tissue. As well, graphene oxide (GO) with relevant biocompatibility features in tissue sites, osseointegration and drug delivery functionalization was fully understood. Besides, the boasting antibacterial ability of silver (Ag) remarkably provided for implantable devices without infection symptoms. Here, surface modification of Ti–6Al–7Nb implants (Ti67IMP) by the development of Ag/GO co-decorated TiO2 NTs was examined. Initially, the anodic TiO2 nanotubes obtained at a constant potential of 60 V were annealed at 600 degree centigrade for 2 h to improve the adhesion of the coating. Afterward, the Ag/GO co-decorated TiO2 NTs were developed by spin coating on Ti67IM. The microstructural features, phase composition and wettability behavior of the nanostructured coating were characterized comparably. In a nutshell, the results of the present study may contribute to the development of the nanostructured Ti67IMP with improved surface properties.

Keywords: anodic tio2 nanotube, biomedical applications, graphene oxide, silver, spin coating

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Authors: Kadir Özsoy

Abstract:

Creating a moderately competitive learning environment is believed to have positive effects on student interest and motivation. The best way today to attract young learners to get involved in a fun, competitive learning experience is possible through mobile applications as these learners mostly rely on games and applications on their phones and tablets to have fun, communicate, look for information and study. In this study, a mobile application called ‘QuizUp’ is used to create a specific game topic for elementary level students at Anadolu University Preparatory School. The topic is specially designed with weekly-added questions in accordance with the course syllabus. Students challenge their classmates or randomly chosen opponents to answer questions related to their course subjects. They also chat and post on the topic’s wall in English. The study aims at finding out students’ perceptions towards the use of the application as a classroom and extra-curricular activity through a survey. The study concludes that educational games boost students’ motivation, lead to increased effort, and positively change their studying habits.

Keywords: competitive learning, educational application, effort, motivation 'QuizUp', study habits

Procedia PDF Downloads 357

Authors: Sourav Sarkar, Manashjit Gogoi

Abstract:

In the evolving landscape of cancer diagnostics, optical biosensing has emerged as a promising tool due to its sensitivity and specificity. This study explores the potential of CdS/ZnS core-shell quantum dots (QDs) capped with 3-Mercaptopropionic acid (3-MPA), which aids in the linking chemistry of QDs to various cancer antibodies. The QDs, with their unique optical and electronic properties, have been integrated into the biosensor design. Their high quantum yield and size-dependent emission spectra have been exploited to improve the sensor’s detection capabilities. The study presents the design of this QD-enhanced optical biosensor. The use of these QDs can also aid multiplexed detection, enabling simultaneous monitoring of different cancer biomarkers. This innovative approach holds significant potential for advancing cancer diagnostics, contributing to timely and accurate detection. Future work will focus on optimizing the biosensor design for clinical applications and exploring the potential of QDs in other biosensing applications. This study underscores the potential of integrating nanotechnology and biosensing for cancer research, paving the way for next-generation diagnostic tools. It is a step forward in our quest for achieving precision oncology.

Keywords: quantum dots, biosensing, cancer, device

Procedia PDF Downloads 56

Authors: Hiba Naccache, Rima Hleiss

Abstract:

Additive manufacturing AM or 3D printing is one of the pillars of Industry 4.0. Compared to traditional manufacturing, AM provides a prototype before production in order to optimize the design and avoid the stock market and uses strictly necessary material which can be recyclable, for the benefit of leaning towards local production, saving money, time and resources. Different types of AM exist and it has a broad range of applications across several industries like aerospace, automotive, medicine, education and else. The Laser Powder Bed Fusion (LPBF) is a metal AM technique that uses a laser to liquefy metal powder, layer by layer, to build a three-dimensional (3D) object. In industry 4.0 and aligned with the numbers 9 (Industry, Innovation and Infrastructure) and 12 (Responsible Production and Consumption) of the Sustainable Development Goals of the UNESCO 2030 Agenda, the AM’s manufacturers committed to minimizing the environmental impact by being sustainable in every production. The LPBF has several environmental advantages, like reduced waste production, lower energy consumption, and greater flexibility in creating components with lightweight and complex geometries. However, LPBF also have environmental drawbacks, like energy consumption, gas consumption and emissions. It is critical to recognize the environmental impacts of LPBF in order to mitigate them. To increase awareness and promote sustainable practices regarding LPBF, the researchers use the Elaboration Likelihood Model (ELM) theory where people from multiple universities in France and Qatar process information in two ways: peripherally and centrally. The peripheral campaigns use superficial cues to get attention, and the central campaigns provide clear and concise information. The authors created a seminar including a video showing LPBF production and a website with educational resources. The data is collected using questionnaire to test attitude about the public awareness before and after the seminar. The results reflected a great shift on the awareness toward LPBF and its impact on the environment. With no presence of similar research, to our best knowledge, this study will add to the literature on the sustainability of the LPBF production technique.

Keywords: additive manufacturing, laser powder bed fusion, elaboration likelihood model theory, sustainable development goals, education-awareness, France, Qatar, specific energy consumption, environmental impact, lightweight components

Procedia PDF Downloads 87

Authors: Marek Maruszczak

Abstract:

Gamified applications have been used successfully in education for years. The rapid development of technologies such as augmented reality and image recognition increases their availability and reduces their prices. Thus, there is an increasing possibility and need for a wide use of such applications in education. The main purpose of this article is to present the effects of work on a mobile application with augmented reality, the aim of which is to motivate tourists to pay more attention to the attractions and increase the likelihood of moving from one attraction to the next while visiting the Palácio Nacional de Sintra in Portugal. Work on the application was carried out together with the employees of Parques de Sintra from 2019 to 2021. Their effect was the preparation of a mobile application using augmented reality and image recognition. The application was tested on the palace premises by both Parques de Sintra employees and tourists visiting Palácio Nacional de Sintra. The collected conclusions allowed for the formulation of good practices and guidelines that can be used when designing gamified apps for the purpose of cultural education.

Keywords: augmented reality, cultural education, gamification, image recognition, mobile games

Procedia PDF Downloads 190