Search results for: fast generalized multi-directional Radon transform

Authors: Victor Chinecherem Ejeke, Raphael Eze Nnam

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The main objective of this research is to produce biodiesel from waste vegetable oil using activated eggshell waste as solid catalysts. A transesterification reaction was performed for the conversion to biodiesel. Waste eggshells were calcined at 700°C, 800°C and 900°C for a time period of 3hrs for the preparation of the renewable catalyst. The calcined waste eggshell catalyst was characterized using X-Ray Florescence (XRF) Spectroscopy, which revealed CaO as the major constituent (90.86%); this was further confirmed by X-Ray Diffraction (XRD) and Fourier Transform Infrared (FTIR) analyses. The prepared catalyst was used for transesterification reaction and the effects of calcination temperature (700 to 900°C), Deep Eutectic Solvent DES loading (3 to 18 wt. %), Waste Egg Shell (WES) catalyst loading (6 to 14 wt. %) on the conversion to biodiesel were studied. The yield of biodiesel using a waste eggshell catalyst (91%) is comparable to conventional catalyst like sodium hydroxide with a yield of 80-90%. The maximum biodiesel production yield was obtained at a specific oil-to methanol molar ratio of 1:10, a temperature of 65°C and a catalyst loading of 14g-wt%. The biodiesel produced was characterized as being composed of methyl Tetradecanoate (C₁₄H₂₈O₂) 30.92% using the Gas Chromatographic (GC-MS) analysis. The fuel properties of the biodiesel (Flashpoint 138ᵒC) were comparable to commercial diesel, and hence it can be used in compression-ignition engines. The results indicated that the catalysts derived from waste eggshell had high potential to be used as biodiesel production catalysts in transesterification of waste vegetable oil with the advantage of reusability and also not requiring water washing steps.

Keywords: waste vegetable oil, catalyst , biodiesel , waste egg shell

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Authors: Aiman Elragig, Hanan Dreiwi, Dung Ly, Idriss Elmabrook

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This paper highlights a new approach to look at online principle components analysis (OPCA). Given a data matrix X ∈ R,^m x n we characterise the online updates of its covariance as a matrix perturbation problem. Up to the principle components, it turns out that online updates of the batch PCA can be captured by symmetric matrix perturbation of the batch covariance matrix. We have shown that as n→ n0 >> 1, the batch covariance and its update become almost similar. Finally, utilize our new setup of online updates to find a bound on the angle distance of the principle components of X and its update.

Keywords: online data updates, covariance matrix, online principle component analysis, matrix perturbation

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Authors: Ugo Galvanetto, Pirto G. Pavan, Mirco Zaccariotto

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The discipline of Computer-integrated surgery (CIS) will provide equipment able to improve the efficiency of healthcare systems and, which is more important, clinical results. Surgeons and machines will cooperate in new ways that will extend surgeons’ ability to train, plan and carry out surgery. Patient specific CIS of the brain requires several steps: 1 - Fast generation of brain models. Based on image recognition of MR images and equipped with artificial intelligence, image recognition techniques should differentiate among all brain tissues and segment them. After that, automatic mesh generation should create the mathematical model of the brain in which the various tissues (white matter, grey matter, cerebrospinal fluid …) are clearly located in the correct positions. 2 – Reliable and fast simulation of the surgical process. Computational mechanics will be the crucial aspect of the entire procedure. New algorithms will be used to simulate the mechanical behaviour of cutting through cerebral tissues. 3 – Real time provision of visual and haptic feedback A sophisticated human-machine interface based on ergonomics and psychology will provide the feedback to the surgeon. The present work will address in particular point 2. Modelling the cutting of soft tissue in a structure as complex as the human brain is an extremely challenging problem in computational mechanics. The finite element method (FEM), that accurately represents complex geometries and accounts for material and geometrical nonlinearities, is the most used computational tool to simulate the mechanical response of soft tissues. However, the main drawback of FEM lies in the mechanics theory on which it is based, classical continuum Mechanics, which assumes matter is a continuum with no discontinuity. FEM must resort to complex tools such as pre-defined cohesive zones, external phase-field variables, and demanding remeshing techniques to include discontinuities. However, all approaches to equip FEM computational methods with the capability to describe material separation, such as interface elements with cohesive zone models, X-FEM, element erosion, phase-field, have some drawbacks that make them unsuitable for surgery simulation. Interface elements require a-priori knowledge of crack paths. The use of XFEM in 3D is cumbersome. Element erosion does not conserve mass. The Phase Field approach adopts a diffusive crack model instead of describing true tissue separation typical of surgical procedures. Modelling discontinuities, so difficult when using computational approaches based on classical continuum Mechanics, is instead easy for novel computational methods based on Peridynamics (PD). PD is a non-local theory of mechanics formulated with no use of spatial derivatives. Its governing equations are valid at points or surfaces of discontinuity, and it is, therefore especially suited to describe crack propagation and fragmentation problems. Moreover, PD does not require any criterium to decide the direction of crack propagation or the conditions for crack branching or coalescence; in the PD-based computational methods, cracks develop spontaneously in the way which is the most convenient from an energy point of view. Therefore, in PD computational methods, crack propagation in 3D is as easy as it is in 2D, with a remarkable advantage with respect to all other computational techniques.

Keywords: computational mechanics, peridynamics, finite element, biomechanics

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Authors: Nuray Güy, Mahmut Özacar

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In the past few decades, considerable attention has been devoted to the photocatalysts for the photocatalytic degradation of environmental pollutants. Many novel nanostructured photocatalysts for wastewater treatment have been investigated, such as TiO2 and, CdS, ZnO and silver halides (AgX, X = Cl, Br, I). The silver halides are photosensitive materials which can absorb photons in the visible region to produce electron–hole pairs. Silver halides are expensive that restricts their applications in large-scale photocatalytic processes. Tannin contains hydroxyl functional groups, it was employed as a modifier to improve the surface properties and adsorption capacity of the activated carbon towards the metal cations uptake. In this work, we designed a new structure of magnetically separable photocatalyst that combines AgCl/ZnO nanoparticles with Fe3O4 nanoparticles deposited on tannin, which was denoted as (AgI/ZnO)-Fe3O4/Tannin. The as-prepared products are characterized by X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), Fourier transform infrared (FTIR), diffuse reflectance spectra (DRS) and vibrating sample magnetometer (VSM). The photocatalyst exhibited high activity degrading a textile dye under visible light irradiation. Moreover, the excellent magnetic property gives a more convenient way to recycle the photocatalysts.

Keywords: AgI/ZnO-Fe3O4/Tannin, visible light, magnetically separable, photocatalyst

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Authors: Muhamad Azuddin Hassan, Siti Shafura Karim, Ambri Mohamed, Iskandar Yahya

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Human serum albumin plays a significant part in the physiological functions of the human body system (HSA).HSA level monitoring is critical for early detection of HSA-related illnesses. The goal of this study is to show that a field effect transistor (FET)-based immunosensor can assess HSA using high aspect ratio carbon nanotubes network (CNT) as a transducer. The CNT network were deposited using air brush technique, and the FET device was made using a shadow mask process. Field emission scanning electron microscopy and a current-voltage measurement system were used to examine the morphology and electrical properties of the CNT network, respectively. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy were used to confirm the surface alteration of the CNT. The detection process is based on covalent binding interactions between an antibody and an HSA target, which resulted in a change in the manufactured biosensor's drain current (Id).In a linear range between 1 ng/ml and 10zg/ml, the biosensor has a high sensitivity of 0.826 mA (g/ml)-1 and a LOD value of 1.9zg/ml.HSA was also identified in a genuine serum despite interference from other biomolecules, demonstrating the CNT-FET immunosensor's ability to quantify HSA in a complex biological environment.

Keywords: carbon nanotubes network, biosensor, human serum albumin

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Authors: Tamas Hartvanyi, Zoltan Andras Nagy, Miklos Szabo

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The dynamic and static capacity are two opposing aspect of warehouse design. Static capacity optimization aims to maximize the space-usage for goods storing, while dynamic capacity needs more free place to handling them. They are opposing by the building structure and the area utilization. According to Pareto principle: the 80% of the goods are the 20% of the variety. From the origin of this statement, it worth to store the big amount of same products by fulfill the space with minimal corridors, meanwhile the rest 20% of goods have the 80% variety of the whole range, so there is more important to be fast-reachable instead of the space utilizing, what makes the space fulfillment numbers worse. The warehouse design decisions made in present practice by intuitive and empiric impressions, the planning method is formed to one selected technology, making this way the structure of the warehouse homogeny. Of course the result can’t be optimal for the inhomogeneous demands. A new innovative model based on our research will be introduced in this paper to describe the technic capacities, what makes possible to define optimal cluster of technology. It is able to optimize the space fulfillment and the dynamic operation together with this cluster application.

Keywords: warehouse, warehouse capacity, warehouse design method, warehouse optimization

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Authors: Christian C. Vaso, Rinlee Butch M. Cervera

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One of the most promising anode materials for solid oxide electrolysis cell (SOEC) application is the Sr-doped LaMnO₃ (LSM) which is known to have a high electronic conductivity but low ionic conductivity. To increase the ionic conductivity or diffusion of ions through the anode, Yttria-stabilized Zirconia (YSZ), which has good ionic conductivity, is proposed to be combined with LSM to create a composite electrode and to obtain a high mixed ionic and electronic conducting anode. In this study, composite of lanthanum strontium manganite and YSZ oxide, La_0.8Sr_0.2MnO₃/Zr_0.92Y_0.08O₂ (LSM/YSZ), with different wt.% compositions of LSM and YSZ were synthesized using solid-state reaction. The obtained prepared composite samples of 60, 50, and 40 wt.% LSM with remaining wt.% of 40, 50, and 60, respectively for YSZ were fully characterized for its microstructure by using powder X-ray diffraction (XRD), Thermogravimetric analysis (TGA), Fourier transform infrared (FTIR), and Scanning electron microscope/Energy dispersive spectroscopy (SEM/EDS) analyses. Surface morphology of the samples via SEM analysis revealed a well-sintered and densified pure LSM, while a more porous composite sample of LSM/YSZ was obtained. Electrochemical impedance measurements at intermediate temperature range (500-700 °C) of the synthesized samples were also performed which revealed that the 50 wt.% LSM with 50 wt.% YSZ (L50Y50) sample showed the highest total conductivity of 8.27x10^-1 S/cm at 600 ^oC with 0.22 eV activation energy.

Keywords: ceramics, microstructure, fuel cells, electrochemical impedance spectroscopy

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Authors: Maja Čović, Josipa Bojčić, Bruna Bacalja, Gorana Jelić Mrčelić

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The appearance of the COVID-19 disease and its fast-spreading brought global pandemic and health crisis. In order to prevent the further spreading of the virus, the governments had implemented mobility restriction rules which left a negative mark on the world’s economy. Although there is numerous research on the impact of COVID-19 on marine traffic around the world, the objective of this paper is to consider the impact of COVID-19 on passenger and cargo traffic in Port of Split, in the Republic of Croatia. Methods used to make the theoretical and research part of the paper are descriptive method, comparative method, compilation, inductive method, deductive method, and statistical method. Paper relies on data obtained via Port of Split Authority and analyses trends in passenger and cargo traffic, including the year 2020, when the pandemic broke. Significant reductions in income, disruptions in transportation and traffic, as well as other maritime services are shown in the paper. This article also observes a significant decline in passenger traffic, cruising traffic and also observes the dynamic of cargo traffic inside the port of Split.

Keywords: COVID-19, pandemic, passenger traffic, ports, trends, cargo traffic

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Authors: Yao Jie, Yeo Khoon Seng

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In recent decades, flapping wing aerodynamics has attracted great interest. Understanding the physics of biological flyers such as birds and insects can help improve the performance of micro air vehicles. The present research focuses on the aerodynamics of insect-like flapping wing flight with the approach of numerical computation. Insect model of hawkmoth is adopted in the numerical study with rigid wing assumption currently. The numerical model integrates the computational fluid dynamics of the flow and active control of wing kinematics to achieve stable flight. The computation grid is a hybrid consisting of background Cartesian nodes and clouds of mesh-free grids around immersed boundaries. The generalized finite difference method is used in conjunction with single value decomposition (SVD-GFD) in computational fluid dynamics solver to study the dynamics of a free hovering hummingbird hawkmoth. The longitudinal dynamics of the hovering flight is governed by three control parameters, i.e., wing plane angle, mean positional angle and wing beating frequency. In present work, a PID controller works out the appropriate control parameters with the insect motion as input. The controller is adjusted to acquire desired maneuvering of the insect flight. The numerical scheme in present study is proven to be accurate and stable to simulate the flight of the hummingbird hawkmoth, which has relatively high Reynolds number. The PID controller is responsive to provide feedback to the wing kinematics during the hovering flight. The simulated hovering flight agrees well with the real insect flight. The present numerical study offers a promising route to investigate the free flight aerodynamics of insects, which could overcome some of the limitations of experiments.

Keywords: aerodynamics, flight control, computational fluid dynamics (CFD), flapping-wing flight

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Authors: Friday Godwin Okibe, Christian Chinweuba Onoyima, Edith Bolanle Agbaji, Victor Olatunji Ajibola

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Polymer-inorganic nanocomposites are presently impacting diverse areas, specifically in biomedical sciences. In this research, hydroxyapatite-sodium alginate has been prepared, and characterized, with emphasis on the influence of sodium alginate on its characteristics. In situ wet chemical precipitation method was used in the preparation. The prepared nanocomposite was characterized with Fourier Transform Infrared spectroscopy (FTIR), Scanning Electron Microscopy (SEM), with image analysis, and X-Ray Diffraction (XRD). The FTIR study shows peaks characteristics of hydroxyapatite and confirmed formation of the nanocomposite via chemical interaction between sodium alginate and hydroxyapatite. Image analysis shows the nanocomposites to be of irregular morphologies which did not show significant change with increasing sodium alginate addition, while particle size decreased with increase in sodium alginate addition (359.46 nm to 109.98 nm). From the XRD data, both the crystallite size and degree of crystallinity also decreased with increasing sodium alginate composition (32.36 nm to 9.47 nm and 72.87% to 1.82% respectively), while the specific surface area and microstrain increased with increasing sodium alginate composition (0.0041 to 0.0139 and 58.99 m²/g to 201.58 m²/g respectively). The results show that the formulation with 50%wt of sodium alginate (HASA-50%wt), possess exceptional characteristics for biomedical applications such as drug delivery.

Keywords: nanocomposite, sodium alginate, hydroxyapatite, biomedical, FTIR, XRD, SEM

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Authors: Mulatu Kassie Birhanu

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Electro-oxidation of glycerol is an important process to convert the less price glycerol into other expensive (essential) and energy-rich chemicals. In this study, nickel was electro-deposited on laboratory-made carbon ceramic electrode (CCE) substrate using electrochemical techniques that is cyclic voltammetry (CV) to prepare an electro-catalyst (Ni/CCE) for electro-oxidation of glycerol. Carbon ceramic electrode was prepared from graphite and methyl tri-methoxy silane (MTMOS) through the processes called hydrolysis and condensation with methanol in acidic media (HCl) by a sol-gel technique. Physico-chemical characterization of bare CCE and modified (deposited) CCE (Ni/CCE) was measured and evaluated by Fourier Transform Infrared spectroscopy (FTIR), Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). Electro-oxidation of glycerol was performed in 0.1 M glycerol in alkaline media (0.5 M NaOH). High-Performance Liquid Chromatography (HPLC) technique was used to identify and determine the concentration of glycerol, reaction intermediates and oxidized products of glycerol after its electro-oxidation is performed. The conversion (%) of electro-oxidation of glycerol during 9-hour oxidation was 73% and 36% at 1.8V and 1.6V vs. RHE, respectively. Formate, oxalate, glycolate and glycerate are the main oxidation products of glycerol with selectivity (%) of 75%, 8.6%, 1.1% and 0.95 % at 1.8 V vs. RHE and 55.4%, 2.2%, 1.0% and 0.6% at 1.6 V vs. RHE respectively. The result indicates that formate is the main product in the electro-oxidation of glycerol on Ni/CCE using the indicated applied potentials.

Keywords: carbon-ceramic electrode, electrodeposition, electro-oxidation, Methyltrimethoxysilane

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Authors: Akrem Sellami, Imed Riadh Farah, Basel Solaiman

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With the development of HyperSpectral Imagery (HSI) technology, the spectral resolution of HSI became denser, which resulted in large number of spectral bands, high correlation between neighboring, and high data redundancy. However, the semantic interpretation is a challenging task for HSI analysis due to the high dimensionality and the high correlation of the different spectral bands. In fact, this work presents a dimensionality reduction approach that allows to overcome the different issues improving the semantic interpretation of HSI. Therefore, in order to preserve the spatial information, the Tensor Locality Preserving Projection (TLPP) has been applied to transform the original HSI. In the second step, knowledge has been extracted based on the adjacency graph to describe the different pixels. Based on the transformation matrix using TLPP, a weighted matrix has been constructed to rank the different spectral bands based on their contribution score. Thus, the relevant bands have been adaptively selected based on the weighted matrix. The performance of the presented approach has been validated by implementing several experiments, and the obtained results demonstrate the efficiency of this approach compared to various existing dimensionality reduction techniques. Also, according to the experimental results, we can conclude that this approach can adaptively select the relevant spectral improving the semantic interpretation of HSI.

Keywords: band selection, dimensionality reduction, feature extraction, hyperspectral imagery, semantic interpretation

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Authors: B. J. Sonani, J. K. Ratnadhariya, Srinivas Palanki

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Cryogenic engineering is the fast growing branch of the modern technology. There are various applications of the cryogenic engineering such as liquefaction in gas industries, metal industries, medical science, space technology, and transportation. The low-temperature technology developed superconducting materials which lead to reduce the friction and wear in various components of the systems. The liquid oxygen, hydrogen and helium play vital role in space application. The liquefaction process is produced very low temperature liquid for various application in research and modern application. The air liquefaction system for oxygen plants in gas industries is based on the Claude cycle. The effect of process parameters on the overall system is difficult to be analysed by manual calculations, and this provides the motivation to use process simulators for understanding the steady state and dynamic behaviour of such systems. The parametric study of this system via MATLAB simulations provide useful guidelines for preliminary design of air liquefaction system based on the Claude cycle. Every organization is always trying for reduce the cost and using the optimum performance of the plant for the staying in the competitive market.

Keywords: cryogenic, liquefaction, low -temperature, oxygen, claude cycle, optimization, MATLAB

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Authors: Pierre Kancir, Jean-Philippe Diguet, Marc Sevaux

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One of the main difficulties in developing multi-robot systems (MRS) is related to the simulation and testing tools available. Indeed, if the differences between simulations and real robots are too significant, the transition from the simulation to the robot won’t be possible without another long development phase and won’t permit to validate the simulation. Moreover, the testing of different algorithmic solutions or modifications of robots requires a strong knowledge of current tools and a significant development time. Therefore, the availability of tools for MRS, mainly with flying drones, is crucial to enable the industrial emergence of these systems. This research aims to present the most commonly used tools for MRS simulations and their main shortcomings and presents complementary tools to improve the productivity of designers in the development of multi-vehicle solutions focused on a fast learning curve and rapid transition from simulations to real usage. The proposed contributions are based on existing open source tools as Gazebo simulator combined with ROS (Robot Operating System) and the open-source multi-platform autopilot ArduPilot to bring them to a broad audience.

Keywords: ROS, ArduPilot, MRS, simulation, drones, Gazebo

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Authors: Juyeon Lee, Sungeun You

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Experiential avoidance is one’s tendency to avoid painful internal experience, unwanted adverse thoughts, emotions, and physical sensations. The Multidimensional Experiential Avoidance Questionnaire (MEAQ) is a measure of experiential avoidance, and the original scale consisted of 62 items with six subfactors including behavioral avoidance, distress aversion, procrastination, distraction/suppression, repression/denial, and distress endurance. The purpose of this study was to examine the factor structure of the MEAQ in a Korean sample. Three hundred community adults and university students aged 18 to 35 participated in an online survey assessing experiential avoidance (MEAQ and Acceptance and Action Questionnaire-II; AAQ-II), depression (Patient Health Questionnaire-9; PHQ-9), anxiety (Generalized Anxiety Disoder-7; GAD-7), negative affect (Positive and Negative Affect Scale; PANAS), neuroticism (Big Five Inventory; BFI), and quality of life (Satisfaction with Life Scale; SWLS). Factor analysis with principal axis with direct oblimin rotation was conducted to examine subfactors of the MEAQ. Results indicated that the six-factor structure of the original scale was adequate. Eight items out of 62 items were removed due to insufficient factor loading. These items included 3 items of behavior avoidance (e.g., “When I am hurting, I would do anything to feel better”), 2 items of repression/denial (e.g., “I work hard to keep out upsetting feelings”), and 3 items of distress aversion (e.g., “I prefer to stick to what I am comfortable with, rather than try new activities”). The MEAQ was positively associated with the AAQ-II (r = .47, p < .001), PHQ-9 (r = .37, p < .001), GAD-7 (r = .34, p < .001), PANAS (r = .35, p < .001), and neuroticism (r = .24, p < .001), and negatively correlated with the SWLS (r = -.38, p < .001). Internal consistency was good for the MEAQ total (Cronbach’s α = .90) as well as all six subfactors (Cronbach’s α = .83 to .87). The findings of the study support the multidimensional feature of experiential avoidance and validity of the MEAQ in a sample of Korean adults.

Keywords: avoidance, experiential avoidance, factor structure, MEAQ

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Authors: Anita Kéri

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Recent developments in the field of education have led to a renewed interest in teaching methodologies and practices. Gamification is fast becoming a key instrument in the education of new generations and besides other methods, serious games have become the center of attention. Ready-built serious games are available for most higher education institutions to buy and implement. However, monetary restraints and the unalterable nature of the games might deter most higher education institutions from the application of these serious games. Therefore, there is a continuously growing need for a customizable serious game that has been developed based on a concrete need analysis and experts’ opinion. There has been little evidence so far of serious games that have been created based on relevant and current need analysis from higher education institution teachers, professional practitioners and students themselves. Therefore, the aim of this current paper is to analyze the needs of higher education institution educators with special emphasis on their needs, the applicability of serious games in their classrooms, and exploring options for the development of a customizable serious game framework. The paper undertakes to analyze workshop discussions on implementing serious games in education and propose a customizable serious game framework applicable in the education of the new generation. Research results show that the most important feature of a serious game is its customizability. The fact that practitioners are able to manage different scenarios and upload their own content to a game seems to be a key to the increasingly widespread application of serious games in the classroom.

Keywords: education, gamification, game-based learning, serious games

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Authors: Apurba Kanti Chowdhury, Taslima Zahan

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The inclusion of mungbean in a cropping pattern not only increases the cropping intensity but also enriches soil health as well as ensures nutrition for the fast-growing population of Bangladesh. A study was conducted in the farmers’ field during 2013-14 and 2014-15 to observe the performance of four-crop based improve cropping pattern Potato-Mungbean-Jute -t.aman rice against the existing cropping pattern Potato-Jute -t.aman rice at Domar, Nilphamari followed by randomized complete block design with three replications. Two years study revealed that inclusion of mungbean and better management practices in improved cropping pattern provided higher economic benefit over the existing pattern by 73.1%. Moreover, the average yield of potato increased in the improved pattern by 64.3% compared to the existing pattern; however yield of jute and t.aman rice in improved pattern declined by 5.6% and 10.7% than the existing pattern, respectively. Nevertheless, the additional yield of mungbean in the improved pattern helped to increase rice equivalent yield of the whole pattern by 38.7% over the existing pattern. Thus, the addition of mungbean in the existing pattern Potato-Jute -t.aman rice seems to be profitable for the farmers and also might be sustainable if the market channel of mungbean developed.

Keywords: crop diversity, food nutrition, production efficiency, yield improvement

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Authors: Hadjadj Abdechafik, Kious Mecheri, Ameur Aissa

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The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the Root Mean Square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an online monitoring system. Although we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal, this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored.

Keywords: flank wear, vibration, milling, signal processing, monitoring

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Authors: Ankur Gupta, Jayant Raj Saurav, Shantanu Bhattacharya

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In this work we report an effective water filtration system based on the photo catalytic performance of semiconducting dense nano-brushes under natural sunlight. During thin-film photocatalysis usually performed by a deposited layer of photocatalyst, a stagnant boundary layer is created near the catalyst which adversely affects the rate of adsorption because of diffusional restrictions. One strategy that may be used is to disrupt this laminar boundary layer by creating a super dense nanostructure near the surface of the catalyst. Further it is adequate to fabricate a structured filter element for a through pass of the water with as grown nanostructures coming out of the surface of such an element. So, the dye remediation is performed through solar means. This remediation was initially limited to lower efficiency because of diffusional restrictions but has now turned around as a fast process owing to the development of the filter materials with standing out dense nanostructures. The effect of increased surface area due to microholes on fraction adsorbed is also investigated and found that there is an optimum value of hole diameter for maximum adsorption.

Keywords: nano materials, photocatalysis, waste water treatment, water remediation

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Authors: Eduarda Dutra De Souza, Gabriela Hammes, Marina Bouzon, Carlos M. Taboada Rodriguez

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The search for minimizing harmful impacts on the environment has become the focus of global society, affecting mainly how to manage organizations. Thus, companies have sought to transform their activities into environmentally friendly initiatives by applying green practices throughout their supply chains. In the logistics domain, the implementation of environmentally sound practices is still in its infancy in emerging countries such as Brazil. Given the need to reduce these environmental damages, this study aims to evaluate the performance of green logistics (GL) in the plastics industry sector in order to help to improve environmental performance within organizations and reduce the impact caused by their activities. The performance tool was based on theoretical research and the use of experts in the field. The Analytic Hierarchy Process (AHP) was used to prioritize green practices and assign weight to the indicators contained in the proposed tool. The tool also allows the co-production of a single indicator. The developed tool was applied in an industry of the plastic packaging sector. However, this tool may be applied in different industry sectors, and it is adaptable to different sizes of companies. Besides the contributions to the literature, this work also presents future paths of research in the field of green logistics.

Keywords: AHP, green logistics, green supply chain, performance evaluation

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Authors: Catherine W. Njeru, Clarence Murithi W., Isaac W. Mwangi, Ruth Wanjau, Grace N. Kiriro, Gerald W. Mbugua

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Flesh from animals is one of the most nutritious food materials that is rich in Vitamin B12, B3 (Niacin), B6, iron, zinc, selenium, and plenty of other vitamins and minerals and a high content of fats Meat consumption projection indicates an increase from 5.5 to 13.3 million tons by 2025 and this demand has been associated with livestock revolution. This study used charcoal flue gases sourced from the combustion of charcoal briquettes to prolong beef shelf life. The FT-IR technique is based on the specific absorption of infrared radiation by carbon monoxide and carbon dioxide molecules. The characterization of the functional groups was done using Fourier transform infrared spectroscopy (Shimadzu IR Tracer-100). The fresh, treated and boiled beef was ground with potassium bromide (KBr) into pellets and analyzed using FT-IR at a range of 400-3600 cm-1. The reaction of fresh, charcoal flue gas treated and boiled beef samples are as shown in the FT-IR spectrums. The fresh and boiled beef spectrums are similar, while the charcoal flue-treated beef samples show distinct peaks at 2100 and 2290 cm-1, which correspond to carbon monoxide and carbon dioxide, respectively. The study proposes the use of FT-IR in the determination of beef for consumption quality studies.

Keywords: FT-IR, charcoal flue gases, beef, charcoal flue gases

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Authors: Qasem Drmosh, Zain Yamai, Amar Mohamedkhair, Abdulmajid Hendi

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In recent years, there has been a growing interest in the reduction of the nitrogen oxides NOx (NO2, NO) gases resulting from automotive or combustion emissions. Recently, metal additives in nanometer dimension onto the surface of SnO2 nanorods, nanowires and nanotubes sensitizer to further increase the sensor response have been used. In contrast, there is a lack study focused on modifying the surface of SnO2 thin films by nanoparticles. The challenge in case of thin films is how to fabricate these nanoparticles on the surfaces in cost-effective method, high purity as well as without hampering electrical and topographical properties. Here in this report, a simple and facile strategy has been demonstrated to acquire high sensitive and fast response NO2 gas sensor. Structural, electrical, morphological, optical, and compositional properties of the fabricated sensors were investigated through different analytical technique including X-ray diffraction (XRD), Field emission scanning emission microscope (FESEM) and X-ray photoelectron spectroscopy (XPS). The sensing performance of the prepared sensors are studied at different temperatures for various concentrations of NO2 and compared with pristine SnO2 film.

Keywords: NO2 sensor, SnO2, sputtering, thin films

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Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: Kaddari Faiza, Mazari Benyounes, Mihoub Youcef, Safa Ahmed

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Active filtering of electric power has now become a mature technology for reactive power and harmonic compensation caused by the proliferation of power electronics devices used for industrial, commercial and residential purposes. The aim of this study is to enhance the power quality by improving the performances of shunt active power filter in harmonic mitigation to obtain sinusoidal source currents with very weak ripples. A power circuit configuration and control scheme for shunt active power filter are described with an improved method for harmonics compensation using self-tuning-filter for harmonics identification and fuzzy logic control to generate reference current. Simulation results (using MATLAB/SIMULINK) illustrates the compensation characteristics of the proposed control strategy. Analysis of these results proves the feasibility and effectiveness of this method to improve the power quality and also show the performances of fuzzy logic control which provides flexibility, high precision and fast response. The total harmonic distortion (THD %) for the simulations found to be within the recommended imposed IEEE 519-1992 harmonic standard.

Keywords: Active Powers Filter (APF), Self-Tuning-Filter (STF), fuzzy logic control, hysteresis-band control

Procedia PDF Downloads 738

Authors: We'aam Alali, Ziad Saffour, Saker Saloum

Abstract:

Low-pressure, sulfur hexafluoride (SF₆) remote radio-frequency (RF) plasma, ignited in a hollow cathode discharge (HCD-L300) plasma system, has been shown to be a powerful method in cotton fabric finishing to achieve water-repellent property. This plasma was ignited at an SF6 flow rate of (200 cm), low pressure (0.5 mbar), and radio frequency (13.56 MHz) with a power of (300 W). The contact angle has been measured as a function of the plasma exposure period using the water contact angle measuring device (WCA), and the changes in the morphology, chemical structure, and mechanical properties as tensile strength and elongation at the break of the fabric have also been investigated using the scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDX), attenuated total reflectance Fourier transform Infrared spectroscopy (ATR-FTIR), and tensile test device, respectively. In addition, weight loss of the fabric and the fastness of washing have been studied. It was found that the exposure period of the fabric to the plasma is an important parameter. Moreover, a good water-repellent cotton fabric can be obtained by treating it with SF₆ plasma for a short time (1 min) without degrading its mechanical properties. Regarding the modified morphology of the cotton fabric, it was found that grooves were formed on the surface of the fibers after treatment. Chemically, the fluorine atoms were attached to the surface of the fibers.

Keywords: cotton fabric, SEM, SF₆ plasma, water-repellency

Procedia PDF Downloads 79

Authors: Iyad A. A. Abusahloub

Abstract:

This research aimed to measure the level of perception and application of Integrated Talent Management according to IBM standards, by the upper and middle categories in Palestinian government institutions in Gaza, using a descriptive-analytical method. Using a questionnaire based on the standards of the IBM Institute for Business Value, the researcher added a second section to measure the perception of integrated talent management, the sample was 248 managers. The SPSS package was used for statistical analysis. The results showed that government institutions in Gaza apply Integrated Talent Management according to IBM standards at a medium degree did not exceed 59.8%, there is weakness in the perception of integrated talent management at the level of 53.6%, and there is a strong correlation between (Integrated Talent Management) and (the perception of the integrated talent management) amounted to 92.9%, and 88.9% of the change in the perception of the integrated talent management is by (motivate and develop, deploy and manage, connect and enable, and transform and sustain) talents, and 11.1% is by other factors. Conclusion: This study concluded that the integrated talent management model presented by IBM with its six dimensions is an effective model to reach your awareness and understanding of talent management, especially that it must rely on at least four basic dimensions out of the six dimensions: 1- Stimulating and developing talent. 2- Organizing and managing talent. 3- Connecting with talent and empowering it. 4- Succession and sustainability of talent. Therefore, this study recommends the adoption of the integrated talent management model provided by IBM to any organization across the world, regardless of its specialization or size, to reach talent sustainability.

Keywords: HR, talent, talent management, IBM

Procedia PDF Downloads 84

Authors: Loïc Chrislin Nguedjio, S. Jerome Afoutou, Rostand Moutou Pitti, Benoit Blaysat, Frédéric Dubois, Naman Recho, Pierre Kisito Talla

Abstract:

The safety and durability of structures remain challenging fields that continue to draw the attention of designers. One widely adopted approach is fracture mechanics, which provides methods to evaluate crack stability in complex geometries and under diverse loading conditions. The global energy approach is particularly comprehensive, as it calculates the energy release rate required for crack initiation and propagation using path-independent integrals. This study aims to extend these invariant integrals to include path-independent integrals, with the goal of enhancing the accuracy of failure predictions. The ultimate objective is to create more robust materials while optimizing structural safety and durability. By integrating the real and virtual field method with the virtual crack closure technique, a new formulation of the M-integral is introduced. This formulation establishes a direct relationship between local stresses on the crack faces and the opening displacements, allowing for an accurate calculation of fracture energy. The analytical calculations are grounded in the assumption that the energy needed to close a crack virtually is equal to the energy released during its opening. This novel integral is implemented in a finite element code using Cast3M to simulate cracking criteria within a wood material context. Initially, the numerical calculations are focused on plane strain conditions, but they are later extended to three-dimensional environments, taking into account the orthotropic nature of wood.

Keywords: energy release rate, path-independent integrals, virtual crack closure, orthotropic material

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Authors: M. S. Abd El-Sadek, Mahmoud A. Omar, Gharib M. Taha

Abstract:

Photodegradation of methylene blue in the presence of tin dioxide (SnO₂) nanoparticles under solar light irradiation are known to be an effective photocatalytic process. In this study, pure and silver (Ag) doped tin dioxide (SnO₂) nanoparticles were prepared at calcination temperature (800ºC) by a modified sol-gel method and studied for their photocatalytic activity with methylene blue as a test contaminant. The characterization of undoped and doped SnO₂ photocatalyst was studied by X-rays diffraction patterns (XRD), transmission electron microscopy (TEM), Fourier Transform Infrared Spectroscopy (FT-IR) and Energy Dispersive X-ray Microanalysis (EDX). The catalytic degradation of methylene blue in aqueous media was studied using UV-Vis spectrophotometer to monitor the degradation process by measuring its absorption spectra. The main absorption peak of methylene blue is observed at λ= 664 nm. The change in the percent of silver in the catalyst affects the photoactivity of SnO₂ on the degradation of methylene blue. The photoactivity of pure SnO₂ was found to be a maximum at dose 0.2 gm of the catalyst with 100 ml of 5 ppm methylene blue in the water. Within 210 min of photodegradation (under sunlight) after leaving the reaction for 90 minutes in the dark to avoid the effect of adsorption, the pure SnO₂ at calcination temperature 800ºC exhibited the best photocatalytic degradation with removal percentage of 93.66% on methylene blue degradation under solar light.

Keywords: SnO₂ nanoparticles, methylene blue degradation, photocatalysis, silver doped-SnO₂

Procedia PDF Downloads 142

Authors: Zarrin Nasri

Abstract:

Microwave irradiation is an innovative technology in the petroleum industry. This kind of energy has been considered to convert vacuum residue of oil refineries into useful products. The advantages of microwaves energy are short time, fast heating, high energy efficiency, and precise process control. In this paper, the effects of catalyst type and amount have been investigated on upgrading of vacuum residue using microwave irradiation. The vacuum residue used in this research is from Tehran oil refinery, Iran. Additives include different catalysts, active carbon as sensitizer, and sodium borohydride as a solid hydrogen donor. Various catalysts contain iron, nickel, molybdenum disulfide, iron oxide and copper. The amount of catalysts in two cases of presence and absence of sodium borohydride have been evaluated. The objective parameters include temperature, asphaltene, viscosity, and API. The specifications of vacuum residue are API, 8.79, viscosity, 16391 cSt (60°C), asphaltene, 13.3 wt %. The results show that there is a significant difference between the effects of catalysts. Among the used catalysts, Fe powder is the best catalyst for upgrading vacuum residue using microwave irradiation and resulted in asphaltene reduction, 31.3 %; viscosity reduction, 76.43 %; and 23.43 % in API increase.

Keywords: asphaltene, microwave, upgrading, vacuum residue, viscosity

Procedia PDF Downloads 255

Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

Procedia PDF Downloads 454