Search results for: engineering applications

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

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Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

Procedia PDF Downloads 155

Authors: Mustafa Gok, Sair Kahraman, Mustafa Fener

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In rock engineering applications, determining uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and basic index properties such as density, porosity, and water absorption is crucial for the design of both underground and surface structures. However, obtaining reliable samples for direct testing, especially from rocks that weather quickly and have low strength, is often challenging. In such cases, indirect methods provide a practical alternative to estimate the physical and mechanical properties of these rocks. In this study, tuff samples collected from the Cappadocia region (Nevşehir) in Turkey were subjected to indirect testing methods. Over 100 tests were conducted, using needle penetrometer index (NPI), point load strength index (PLI), and disc shear index (BPI) to estimate the uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), density, and water absorption index of the tuffs. The relationships between the results of these indirect tests and the target physical properties were evaluated using simple and multiple regression analyses. The findings of this research reveal strong correlations between the indirect methods and the mechanical properties of the tuffs. Both uniaxial compressive strength and Brazilian tensile strength could be accurately predicted using NPI, PLI, and BPI values. The regression models developed in this study allow for rapid, cost-effective assessments of tuff strength in cases where direct testing is impractical. These results are particularly valuable for geological engineering applications, where time and resource constraints exist. This study highlights the significance of using indirect methods as reliable predictors of the mechanical behavior of weak rocks like tuffs. Further research is recommended to explore the application of these methods to other rock types with similar characteristics. Further research is required to compare the results with those of established direct test methods.

Keywords: brazilian tensile strength, disc shear strength, indirect methods, tuffs, uniaxial compressive strength

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Authors: Arpan Dwivedi, Yogesh Pahariya

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In this paper, optimal design of hybrid standalone power supply system (SAPS) is done for off grid applications in remote areas where transmission of power is difficult. The hybrid SAPS system uses two primary energy sources, wind and solar, and in addition to these diesel generator is also connected to meet the load demand in case of failure of wind and solar system. This paper presents mathematical modeling of 1.4 MW hybrid SAPS system for rural electrification. This paper firstly focuses on mathematical modeling of PV module connected in a string, secondly focuses on modeling of permanent magnet wind turbine generator (PMWTG). The hybrid controller is also designed for selection of power from the source available as per the load demand. The power output of hybrid SAPS system is analyzed for meeting load demands at urban as well as for rural areas.

Keywords: SAPS, DG, PMWTG, rural area, off-grid, PV module

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Authors: Elif Tugce Aksun Tumerkan

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Fluorescent proteins (FPs) have become very popular since green fluorescent protein discovered from crystal jellyfish. It is known that Anthozoa species have a wide range of chromophore organisms, and the initial crystal structure for non-fluorescent chromophores obtained from the reef-building coral has been determined. There are also differently coloured pigments in non-bioluminescent Anthozoa zooxanthellate and azooxanthellate which are frequently members of the GFP-like protein family. The development of fluorescent proteins (FPs) and their applications is an outstanding example of basic science leading to practical biotechnological and medical applications. Fluorescent proteins have several applications in science and are used as important indicators in molecular biology and cell-based research. With rising interest in cell biology, FPs have used as biosensor indicators and probes in pharmacology and cell biology. Using fluorescent proteins in genetically encoded metabolite sensors has many advantages than chemical probes for metabolites such as easily introduced into any cell or organism in any sub-cellular localization and giving chance to fixing to fluoresce of different colours or characteristics. There are different factors effects to signalling mechanism when they used as a biosensor. While there are wide ranges of research have been done on the significance and applications of fluorescent proteins, the cell signalling response of FPs and target cell are less well understood. In this study, it was aimed to clarify the response of adaptive mechanisms of coral species such as pH, temperature and symbiotic relationship and target cells properties on the signalling capacity. Corals are a rich natural source of fluorescent proteins that change with environmental conditions such as light, heat stress and injury. Adaptation mechanism of coral species to these types of environmental variations is important factor due to FPs properties have affected by this mechanism. Since fluorescent proteins obtained from nature, their own ecological property like the symbiotic relationship is observed very commonly in coral species and living conditions have the impact on FPs efficiency. Target cell properties also have an effect on signalling and visualization. The dynamicity of detector that used for reading fluorescence and the level of background fluorescence are key parameters for the quality of the fluorescent signal. Among the factors, it can be concluded that coral species adaptive characteristics have the strongest effect on FPs signalling capacity.

Keywords: biosensor, cell biology, environmental conditions, fluorescent protein, sea anemone

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Authors: Venkatesan Annadurai, Kannan Ethirajalu, Anu Roshini Ramakrishnan

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Copper oxide (CuO) and zinc oxide (ZnO) based coaxial (CuO-ZnO nanorods) heterojunction has been the interest of various research communities for solar cells, light emitting diodes (LEDs) and photodetectors applications. Copper oxide (CuO) is a p-type material with the band gap of 1.5 eV and it is considered to be an attractive absorber material in solar cells applications due to its high absorption coefficient and long minority carrier diffusion length. Similarly, n-type ZnO nanorods possess many attractive advantages over thin films such as, the light trapping ability and photosensitivity owing to the presence of oxygen related hole-traps at the surface. Moreover, the abundant availability, non-toxicity, and inexpensiveness of these materials make them suitable for potentially cheap, large area, and stable photovoltaic applications. However, the efficiency of the CuO-ZnO nanorods heterojunction based devices is greatly affected by interface defects which generally lead to the poor performance. In spite of having much potential, not much work has been carried out to understand the interface quality and transport mechanism involved across the CuO-ZnO nanorods heterojunction. Therefore, a detailed investigation of CuO-ZnO heterojunction is needed to understand the interface which affects its photovoltaic performance. Herein, we have fabricated the CuO-ZnO nanorods based heterojunction by simple hydrothermal and electrodeposition technique and investigated its interface quality by carrying out temperature (300 –10 K) dependent current-voltage (I-V) measurements under dark and illumination of visible light. Activation energies extracted from the temperature dependent I-V characteristics reveals that recombination and tunneling mechanism across the interfacial barrier plays a significant role in the current flow.

Keywords: heterojunction, electrical transport, nanorods, solar cells

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Authors: Ingy N. Bkrey, Ahmed A. Moniem

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We succeeded to produce a high performance and flexible graphene/Manganese dioxide (G/MnO2) electrode coated on flexible polyethylene terephthalate (PET) substrate. The graphene film is initially synthesized by drop-casting the graphene oxide (GO) solution on the PET substrate, followed by simultaneous reduction and patterning of the dried film using carbon dioxide (CO2) laser beam with power of 1.8 W. Potentiostatic Anodic Deposition method was used to deposit thin film of MnO2 with different loading mass 10 – 50 and 100 μg.cm-2 on the pre-prepared graphene film. The electrodes were fully characterized in terms of structure, morphology, and electrochemical performance. A maximum specific capacitance of 973 F.g-1 was attributed when depositing 50 μg.cm-2 MnO2 on the laser reduced graphene oxide rGO (or G/50MnO2) and over 92% of its initial capacitance was retained after 1000 cycles. The good electrochemical performance and long-term cycling stability make our proposed approach a promising candidate in the supercapacitor applications.

Keywords: electrode deposition, flexible, graphene oxide, graphene, high power CO2 Laser, MnO2

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Authors: Ta-Huang Sun, Ming-Hao Hsieh, Min-Chuan Wang, Der-Jun Jan

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Electrochromism refers to the persistent and reversible change of optical properties by an applied voltage pulse. There are many transition metal oxides exhibiting electrochromism, e.g. oxides of W, Ni, Ir, V, Ti, Co and Mo. Organic materials especially some conducting polymers such as poly(aniline), poly(3, 4-propylene- dioxythiophene) also received much attention for electrochromic (EC) applications. Electrochromic materials attract considerable interest because of their potential applications, such as information displays, smart windows, variable reflectance mirrors, and variable-emittance thermal radiators. In this study, the EC characteristics are investigated on an all-solid-state EC device composed of a-WO₃ and Ni(OH)₂ with a Ta₂O₅ protective layer which is prepared by magnetron sputtering. It is found that the transmittance modulation increases with decreasing the film thickness of Ta₂O₅. On the other hand, the transmittance modulation is 57% as the Ni(OH)₂/ITO is prepared by the linear-sweep potential cycling of the sputter-deposited Ta₂O₅/NiO/ITO in a 0.5 M LiClO₄+H₂O electrolyte. However, when Ni(OH)₂/ITO is prepared by a 0.01 M HCl electrolyte, the transmittance modulation of EC device can be improved to 61%.

Keywords: electrochromic device, tungsten oxide, nickel, Ta₂O₅

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Authors: Aldan A. Sapargaliyev, Yerbol A. Sapargaliyev

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Since the invention, the electric machine (EM) can be defined as oEM – one-vector electric machine, as it works due to one-vector inductive coupling with use of one-vector electromagnet. The disadvantages of oEM are large size and limited efficiency at low and medium power applications. This paper describes multi-vector electric machine (mEM) based on multi-vector inductive coupling, which is characterized by the increased surface area of ​​the inductive coupling per EM volume, with a reduced share of inefficient and energy-consuming part of the winding, in comparison with oEM’s. Particularly, it is considered, calculated and compared the performance of three different electrical motors and their power at the same volumes and rotor frequencies. It is also presented the result of calculation of correlation between power density and volume for oEM and mEM. The method of multi-vector inductive coupling enables mEM to possess 1.5-4.0 greater density of power per volume and significantly higher efficiency, in comparison with today’s oEM, especially in low and medium power applications. mEM has distinct advantages, when used in transport vehicles such as electric cars and aircrafts.

Keywords: electric machine, electric motor, electromagnet, efficiency of electric motor

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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: Lian Yang

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Object-oriented programming (OOP) is the dominant programming paradigm in today’s software industry and it has literally enabled average software developers to develop millions of commercial strength software applications in the era of INTERNET revolution over the past three decades. On the other hand, the lack of strict mathematical model and domain constraint features at the language level has long perplexed the computer science academia and OOP engineering community. This situation resulted in inconsistent system qualities and hard-to-understand designs in some OOP projects. The difficulties with regards to fix the current situation are also well known. Although the power of OOP lies in its unbridled flexibility and enormously rich data modeling capability, we argue that the ambiguity and the implicit facade surrounding the conceptual model of a class and an object should be eliminated as much as possible. We listed the five major usage of class and propose to separate them by proposing new language constructs. By using well-established theories of set and FSM, we propose to apply certain simple, generic, and yet effective constraints at OOP language level in an attempt to find a possible solution to the above-mentioned issues regarding OOP. The goal is to make OOP more theoretically sound as well as to aid programmers uncover warning signs of irregularities and domain-specific issues in applications early on the development stage and catch semantic mistakes at runtime, improving correctness verifiability of software programs. On the other hand, the aim of this paper is more practical than theoretical.

Keywords: new language constructs, set theory, FSM theory, user defined value type, function groups, membership qualification attribute (MQA), check-constraint (CC)

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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: Haya Sammana

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A well-defined curricula must be adopted to meet the increasing complexity and diversity in the software applications. In reality, some IT majors such as computer science and computer engineering receive the software engineering education in a single course which is considered as a big challenged for the instructors and universities. Also, it requires students to gain the most of practical experiences that simulate the real work in software companies. Furthermore, we have noticed that there is no consensus on how, when and what to teach in that introductory course to gain the practical experiences that are required by the software companies. Because all of software engineering disciplines will not fit in just one course, so the course needs reasonable choices in selecting its topics. This arises an important question which is an essential one to ask: Is this course has the ability to formulate a true software engineer that meets the needs of industry? This question arises a big challenge in selecting the appropriate topics. So answering this question is very important for the next undergraduate students. During teaching this course in the curricula, the feedbacks from an undergraduate students and the keynotes of the annual meeting for an advisory committee from industrial side provide a probable answer for the proposed question: it is impossible to build a true software engineer who possesses all the essential elements of software engineering education such teamwork, communications skills, project management skills and contemporary industrial practice from one course and it is impossible to have a one course covering all software engineering topics. Besides the used teaching approach, the author proposes an implemented three supportive ways aiming for mitigating the expected risks and increasing the opportunity to build a true software engineer.

Keywords: software engineering course, software engineering education, software experience, supportive approach

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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

Abstract:

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

Procedia PDF Downloads 324

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

Abstract:

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

Procedia PDF Downloads 107

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

Abstract:

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

Procedia PDF Downloads 386

Authors: Chih-Hsin Lin, Shyh-Yuan Lee, Yuan-Min Lin

Abstract:

For many tissue engineering applications, an important goal is to create functional tissues in-vitro, and such tissues to be viable, they have to be vascularized. Endothelial cells (EC) and endothelial progenitor cells (EPC) are promising candidates for vascularization. However, both of them have limited expansion capacity and autologous cells currently do not exist for either ECs or EPCs. Therefore, we use bone marrow mesenchymal stem cells (MSC) as a source material for ECs. Growth supplements are commonly used to induce MSC differentiation, and further improvements in differentiation conditions can be made by modifying the cell's growth environment. An example is pre-treatment of the growth dish with gas plasma, in order to modify the surface functional groups of the material that the cells are seeded on. In this work, we compare the effects of different gas plasmas on the growth and differentiation of MSCs. We treat the dish with different plasmas (CO2, N2, and O2) and then induce MSC differentiation with endothelial growth medium-2 (EGM-2). We find that EGM-2 by itself upregulates EC marker CD31 mRNA expression, but not VEGFR2, CD34, or vWF. However, these additional EC marker expressions were increased for cells seeded on plasma treated substrates. Specifically, for EC markers, we found that N2 plasma treatment upregulated CD31 and VEGFR-2 mRNA expressions; CO2 plasma treatment upregulated CD34 and vWF mRNA expressions. The osteogenic markers ALP and osteopontin mRNA expressions were markedly enhanced on all plasma-treated dishes. We also found that plasma treatment in conjunction with EGM-2 growth medium can enhance MSCs differentiation into endothelial-like cells and osteogenic-like cells. Our work shows that the effect of the growth medium (EGM-2) on MSCs differentiation is influenced by the plasma modified surface chemistry of the substrate. In conclusion, plasma surface modification can enhance EGM-2 effectiveness and induced both endothelial and osteogenic differentiation. Our findings provide a method to enhance EGM-2 based cell differentiation, with consequences for tissue engineering and stem cell biology applications.

Keywords: endothelial differentiation, EGM-2, osteogenesis, plasma treatment, surface modification

Procedia PDF Downloads 331

Authors: Neeta Kumari, Gopal Pathak

Abstract:

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

Procedia PDF Downloads 550