Search results for: robust optimization

Authors: Muhammad Awais Kiani, Abdul Basit Kiani, Maryam Kiani

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Synergizing Sales and Marketing for Electronics Engineering with Web Development, explores the dynamic relationship between sales, marketing, and web development within the electronics engineering industry. This study is important for the power of digital platforms to connect with customers. Which increases brand visibility and drives sales. It highlights the need for collaboration between sales and marketing teams, as well as the integration of web development strategies to create seamless user experiences and effective lead generation. Furthermore, It also emphasizes the role of data analytics and customer insights in optimizing sales and marketing efforts in the ever-evolving landscape of electronics engineering. Sales and marketing play a crucial role in driving business growth, and in today's digital landscape, web development has become an integral part of these strategies. Web development enables businesses to create visually appealing and user-friendly websites that effectively showcase their products or services. It allows for the integration of e-commerce functionalities, enabling seamless online transactions. Furthermore, web development helps businesses optimize their online presence through search engine optimization (SEO) techniques, social media integration, and content management systems. This abstract highlights the symbiotic relationship between sales marketing in the electronics industry and web development, emphasizing the importance of a strong online presence in achieving business success.

Keywords: electronics industry, web development, sales, marketing

Procedia PDF Downloads 87

Authors: A. Aravind, M. Vetrivel, P. Abhimanyu, C. A. Akaash Emmanuel Raj, K. Sundararaj, V. R. S. Kumar

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The choice of high-speed, low budget hatchback car with diversified options is increasing for meeting the new generation buyers trend. This paper is aimed to augment the current speed of the hatchback cars through the aerodynamic drag reduction technique. The inverted airfoils are facilitated at the bottom of the car for generating the downward force for negating the lift while increasing the current speed range for achieving a better road performance. The numerical simulations have been carried out using a 2D steady pressure-based    k-ɛ realizable model with enhanced wall treatment. In our numerical studies, Reynolds-averaged Navier-Stokes model and its code of solution are used. The code is calibrated and validated using the exact solution of the 2D boundary layer displacement thickness at the Sanal flow choking condition for adiabatic flows. We observed through the parametric analytical studies that the inverted airfoil integrated with the bottom surface at various predesigned locations of Hatchback cars can improve its overall aerodynamic efficiency through drag reduction, which obviously decreases the fuel consumption significantly and ensure an optimum road performance lucratively with maximum permissible speed within the framework of the manufactures constraints.

Keywords: aerodynamics of commercial cars, downward force, hatchback car, inverted airfoil

Procedia PDF Downloads 251

Authors: Ghebremedhin Tsegay, Weldu Tesfagaber, Yuanmao Zhu, Xijun He, Wan Wang, Zhenjiang Zhang, Encheng Sun, Jinya Zhang, Yuntao Guan, Fang Li, Renqiang Liu, Zhigao Bu, Dongming Zhao*

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African swine fever (ASF) is a highly infectious viral disease of pigs, resulting in significant economic loss worldwide. As there is no approved vaccines and treatments, the control of ASF entirely depends on early diagnosis and culling of infected pigs. Thus, highly specific and sensitive diagnostic assays are required for accurate and early diagnosis of ASF virus (ASFV). Currently, only a few recombinant proteins have been tested and validated for use as reagents in ASF diagnostic assays. The most promising ones for ASFV antibody detection were p72, p30, p54, and pp62. So far, three ELISA kits based on these recombinant proteins have been commercialized. Due to the complex nature of the virus and variety forms of the disease, robust serodiagnostic assays are still required. ASFV p22 protein, encoded by KP177R gene, is located in the inner membrane of viral particle and appeared transiently in the plasma membrane early after virus infection. The p22 protein interacts with numerous cellular proteins, involved in processes of phagocytosis and endocytosis through different cellular pathways. However, p22 does not seem to be involved in virus replication or swine pathogenicity. In this study, E.coli expressed recombinant p22 protein was used to generate a monoclonal antibody (mAb), and its potential use for the development of blocking ELISA (bELISA) was evaluated. A total of 806 pig serum samples were tested to evaluate the bELISA. Acording the ROC (Reciever operating chracteristic) analysis, 100% sensitivity and 98.10% of specificity was recorded when the PI cut-off value was set at 47%. The novel assay was able to detect the antibodies as early as 9 days post infection. Finaly, a highly sensitive, specific and rapid novel p22-mAb based bELISA assay was developed, and optimized for detection of antibodies against genotype I and II ASFVs. It is a promising candidate for an early and acurate detection of the antibodies and is highly expected to have a valuable role in the containment and prevention of ASF.

Keywords: ASFV, blocking ELISA, diagnosis, monoclonal antibodies, sensitivity, specificity

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Authors: Ghada Badr, Manar Hosny, Nuha Bintayyash, Eman Albilali, Souad Larabi Marie-Sainte

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The median problem is significantly applied to derive the most reasonable rearrangement phylogenetic tree for many species. More specifically, the problem is concerned with finding a permutation that minimizes the sum of distances between itself and a set of three signed permutations. Genomes with equal number of genes but different order can be represented as permutations. In this paper, an algorithm, namely BeamGA median, is proposed that combines a heuristic search approach (local beam) as an initialization step to generate a number of solutions, and then a Genetic Algorithm (GA) is applied in order to refine the solutions, aiming to achieve a better median with the smallest possible reversal distance from the three original permutations. In this approach, any genome rearrangement distance can be applied. In this paper, we use the reversal distance. To the best of our knowledge, the proposed approach was not applied before for solving the median problem. Our approach considers true biological evolution scenario by applying the concept of common intervals during the GA optimization process. This allows us to imitate a true biological behavior and enhance genetic approach time convergence. We were able to handle permutations with a large number of genes, within an acceptable time performance and with same or better accuracy as compared to existing algorithms.

Keywords: median problem, phylogenetic tree, permutation, genetic algorithm, beam search, genome rearrangement distance

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Authors: Nabil Mezhoud

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The economic operation of electric energy generating systems is one of the predominant problems in energy systems. Due to the need for better reliability, high energy quality, lower losses, lower cost and a clean environment, the application of renewable and sustainable energy sources, such as wind energy, solar energy, etc., in recent years has become more widespread. In this work, one of a bio-inspired meta-heuristic algorithm inspired by the flashing behavior of fireflies at night called the Firefly Algorithm (FFA) is applied to solve the Optimal Energy Management (OEM) and the environmental index (EI) problems of a micro-grid (MG) operating by Renewable and Sustainable Generation Systems (RSGS). Our main goal is to minimize the nonlinear objective function of an electrical microgrid, taking into account equality and inequality constraints. The FFA approach was examined and tested on a standard MG system composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), and non-renewable energy, such as fuel cells (FC), micro turbine (MT), diesel generator (DEG) and loads with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of the proposed approach to solve the OEM and the EI problems. The results of the proposed method have been compared and validated with those known references published recently.

Keywords: renewable energy sources, energy management, distributed generator, micro-grids, firefly algorithm

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Authors: Vladyslav Povoroznyuk, Oksana Ivanyk, Nataliia Dzerovych

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In the diagnostics of osteoporosis, the gold standard is considered to be bone mineral density; however, X-ray densitometry is not an accurate indicator of osteoporotic fracture risk under all circumstances. In this regard, the search for new methods that could determine the indicators not only of the mineral density, but of the bone tissue quality, is a logical step for diagnostic optimization. One of these methods is the evaluation of trabecular bone quality. The aim of this study was to examine the quality and mineral density of spine bone tissue, femoral neck, and body composition of women depending on the duration of the postmenopausal period, to determine the correlation of body fat with indicators of bone mineral density and quality. The study examined 179 women in premenopausal and postmenopausal periods. The patients were divided into the following groups: Women in the premenopausal period and women in the postmenopausal period at various stages (early, middle, late postmenopause). A general examination and study of the above parameters were conducted with General Electric X-ray densitometer. The results show that bone quality and mineral density probably deteriorate with advancing of postmenopausal period. Total fat and lean mass ratio is not likely to change with age. In the middle and late postmenopausal periods, the bone tissue mineral density of the spine and femoral neck increases along with total fat mass.

Keywords: osteoporosis, bone tissue mineral density, bone quality, fat mass, lean mass, postmenopausal osteoporosis

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Authors: Sandeep Mohan Ahuja, Gulshan Kumar Jawa

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Cyclone separators are crucial components in various industries tasked with efficiently separating particulate matter from gas streams. Achieving optimal performance hinges on a deep understanding of flow dynamics and particle behaviour within these separators. In this investigation, Computational Fluid Dynamics (CFD) simulations are conducted utilizing the Discrete Phase Model (DPM) to dissect the intricate flow patterns, particle trajectories, and separation efficiency within cyclone separators. The study delves into the influence of pivotal parameters like inlet velocity, particle size distribution, and cyclone geometry on separation efficiency. Through numerical simulations, a comprehensive comprehension of fluid-particle interaction phenomena within cyclone separators is attained, allowing for the assessment of solid collection efficiency across diverse operational conditions and geometrical setups. The insights gleaned from this study promise to advance our understanding of the complex interplay between fluid and particle within cyclone separators, thereby enabling optimization across a wide array of industrial applications. By harnessing the power of CFD simulations and the DPM, this research endeavours to furnish valuable insights for designing, operating, and evaluating the performance of cyclone separators, ultimately fostering greater efficiency and environmental sustainability within industrial processes.

Keywords: cyclone separator, computational fluid dynamics, enhancing efficiency, discrete phase model

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Olivier Mesly

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This research presents a conceptual framework termed “Consumer Financial Spinning” (CFS) to analyze consumer behavior in the financial/economic markets. This phenomenon occurs when consumers of high-stakes financial products accumulate unsustainable debt, leading them to detach from their initial financial hierarchy of needs, wealth-related goals, and preferences regarding their household portfolio of assets. The daring actions of these consumers, forming a dark financial triangle, are characterized by three behaviors: overconfidence, the use of rationed rationality, and deceitfulness. We show that we can incorporate CFS into the traditional CAPM and Markovitz’ portfolio optimization models to create a framework that explains such market phenomena as the global financial crisis, highlighting the antecedents and consequences of ill-conceived speculation. Because this is a conceptual paper, there is no methodology with respect to ground studies. However, we apply modeling principles derived from the data percolation methodology, which contains tenets explicating how to structure concepts. A simulation test of the proposed framework is conducted; it demonstrates the conditions under which the relationship between expected returns and risk may deviate from linearity. The analysis and conceptual findings are particularly relevant both theoretically and pragmatically as they shed light on the psychological conditions that drive intense speculation, which can lead to market turmoil. Armed with such understanding, regulators are better equipped to propose solutions before the economic problems become out of control.

Keywords: consumer financial spinning, rationality, deceitfulness, overconfidence, CAPM

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using six sigma methodologies to reach the desired shrinkage of a manufactured high-density polyurethane (HDPE) part produced by the injection molding machine. It presents a case study where the correct shrinkage is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for an injection molding process. To improve this process and keep the product within specifications, the six sigma methodology, design, measure, analyze, improve, and control (DMAIC) approach, was implemented in this study. The six sigma approach was paired with the Taguchi methodology to identify the optimized processing parameters that keep the shrinkage rate within the specifications by our customer. An L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of the cooling time, melt temperature, holding time, and metering stroke. The noise factor is the difference between material brand 1 and material brand 2. After the confirmation run was completed, measurements verify that the new parameter settings are optimal. With the new settings, the process capability index has improved dramatically. The purpose of this study is to show that the six sigma and Taguchi methodology can be efficiently used to determine important factors that will improve the process capability index of the injection molding process.

Keywords: injection molding, shrinkage, six sigma, Taguchi parameter design

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Authors: Gargi Ghoshal, Ashay Jain

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Microencapsulation of β-carotene was optimized by complex coacervation technique using casein/gum tragacanth (CAS/GT) coating as a function of pH, initial protein to polysaccharide mixing ratio (Pr:Ps), total biopolymer concentration, core material load, zeta potential, and ionic strength. This study was aimed to understand the influence of experimental parameters on the coacervation kinetics, the coacervate yield, and entrapment efficiency. At a Pr:Ps = 2:1, an optimum pH of complex coacervation was found 4.35, at which the intensity of electrostatic interaction was maximum. At these ratios of coating, the phase separation occurred the fastest and the final coacervate yield and entrapment efficiency was the highest. Varying the Pr: Ps shifted the value of optimum pH. This incident was due to the level of charge compensation of the CAS/GT complexes. Finally, electrostatic interaction and formation of coacervates between CAS and GT were confirmed by Fourier transform infra-red (FTIR) spectra. The size and surface properties of coacervates were studied using scanning electron microscopy (SEM). The resultant formulation (β-carotene loaded microcapsules) was evaluated for in vitro release study and antioxidant activity. Stability of encapsulated β-carotene was also evaluated under three levels of temperature (5, 25 and 40 °C) for 3 months. Encapsulation strongly increased the stability of micronutrients. Our results advocate potential of microcapsules as a novel carrier for the safeguard and sustained release of micronutrient.

Keywords: β-carotene, casein, complex coacervation, controlled release, gum tragacanth, microcapsules

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Komal Verma, V. S. Moholkar

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This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result is essentially a consequence of synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Microconvection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe₃O₄@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater The Fe₃O₄@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: Fe₃O₄@AC nanocomposite, RSM, COD;, LC-MS, Toxicity

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Authors: Lila Boulekbache-Makhlouf, Kahina Djaoud, Myriam Tazarourte, Samir Hadjal, Khodir Madani

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In Algeria, important quantities of secondary date variety (Phoenix dactylifera L.) are generated in each campaign; their chemical composition is similar to that of commercial dates. The present work aims to valorize this common date variety (Degla-Beida) which is often poorly exploited. In this context, we tried to prepare syrup from the secondary date variety and to evaluate the effect of conventional extraction (CE) or water bath extraction (WBE) and alternative extraction (microwaves assisted extraction (MAE), and ultrasounds assisted extraction (UAE)) on its total sugar content (TSC), using response surface methodology (RSM). Then, the analysis of individual sugars was performed by high-performance liquid chromatography (HPLC). Maximum predicted TSC recoveries under the optimized conditions for MAE, UAE and CE were 233.248 ± 3.594 g/l, 202.889 ± 5.797 g/l, and 233.535 ± 5.412 g/l, respectively, which were close to the experimental values: 233.796 ± 1.898 g/l; 202.037 ± 3.401 g/l and 234.380 ± 2.425 g/l. HPLC analysis revealed high similarity in the sugar composition of date juices obtained by MAE (60.11% sucrose, 16.64% glucose and 23.25% fructose) and CE (50.78% sucrose, 20.67% glucose and 28.55% fructose), although a large difference was detected for that obtained by UAE (0.00% sucrose, 46.94% glucose and 53.06% fructose). Microwave-assisted extraction was the best method for the preparation of date syrup with an optimal recovery of total sugar content. However, ultrasound-assisted extraction was the best one for the preparation of date syrup with high content of reducing sugars.

Keywords: dates, extraction, RSM, sugars, syrup

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Authors: Ganesh Dattatraya Saratale, Min Kyu Oh

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Rice straw is one of the most abundant lignocellulosic waste materials and its annual production is about 731 Mt in the world. This study treats the subject of effective utilization of this waste biomass for biofuels production. We have showed a comparative assessment of numerous pretreatment strategies for rice straw, comprising of major physical, chemical and physicochemical methods. Among the different methods employed for pretreatment alkaline pretreatment in combination with sodium chlorite/acetic acid delignification found efficient pretreatment with significant improvement in the enzymatic digestibility of rice straw. A cellulase dose of 20 filter paper units (FPU) released a maximum 63.21 g/L of reducing sugar with 94.45% hydrolysis yield and 64.64% glucose yield from rice straw, respectively. The effects of different pretreatment methods on biomass structure and complexity were investigated by FTIR, XRD and SEM analytical techniques. Finally the enzymatic hydrolysate of rice straw was used for ethanol production using developed Saccharomyces cerevisiae SR8. The developed yeast strain enabled efficient fermentation of xylose and glucose and produced higher ethanol production. Thus development of bioethanol production from lignocellulosic waste biomass is generic, applicable methodology and have great implication for using ‘green raw materials’ and producing ‘green products’ much needed today.

Keywords: rice straw, pretreatment, enzymatic hydrolysis, FPU, Saccharomyces cerevisiae SR8, ethanol fermentation

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Authors: Hao Qu, Xiang Liu, Michael Crosby, Brian Kozak, Andreas K. Freund

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The outstanding performance of highly oriented pyrolytic graphite (HOPG) as an optical element for neutron beam conditioning is unequaled by any other crystalline material in the applications of monochromator, analyzer, and filter. This superiority stems from the favorable nuclear properties of carbon (small absorption and incoherent scattering cross-sections, big coherent scattering length) and the specific crystalline structure (small thermal diffuse scattering cross-section, layered crystal structure). The real crystal defect structure revealed by imaging techniques is correlated with the parameters used in the mosaic model (mosaic spread, mosaic block size, uniformity). The diffraction properties (rocking curve width as determined by both the intrinsic mosaic spread and the diffraction process, peak and integrated reflectivity, filter transmission) as a function of neutron wavelength or energy can be predicted with high accuracy and reliability by diffraction theory using empirical primary extinction coefficients extracted from a great amount of existing experimental data. The results of these calculations are given as graphs and tables permitting to optimize HOPG characteristics (mosaic spread, thickness, curvature) for any given experimental situation.

Keywords: neutron optics, pyrolytic graphite, mosaic spread, neutron scattering, monochromator, analyzer

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Ogan Karabas, Suleyman Yigit

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Number of blade and blade type of centrifugal fans are the most decisive factor on the field of application, noise level, suction pressure and outlet mass flow rate. Nowadays, in order to determine these effects on centrifugal fans, numerical studies are carried out in addition to experimental studies. In this study, it is aimed to numerically investigate the changes of suction pressure and outlet mass flow rate values of a centrifugal fan according to the number of blade and blade type. Centrifugal fans of the same size with forward, backward and straight blade type were analyzed by using a simulation program and compared with each other. This analysis was carried out under steady state condition by selecting k-Ɛ turbulence model and air is assumed incompressible. Then, 16, 32 and 48 blade centrifugal fans were again analyzed by using same simulation program, and the optimum number of blades was determined for the suction pressure and the outlet mass flow rate. According to the results of the analysis, it was obtained that the suction pressure in the 32 blade fan was twice the value obtained in the 16 blade fan. In addition, the outlet mass flow rate increased by 45% with the increase in the number of blade from 16 to 32. There is no significant change observed on the suction pressure and outlet mass flow rate when the number of blades increased from 32 to 48. In the light of the analysis results, the optimum blade number was determined as 32.

Keywords: blade type, centrifugal fan, cfd, outlet mass flow rate, suction pressure

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Authors: Julius Niba Fon, Jean Hude E. Moudingo

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Mangrove ecosystems in Cameroon are valuable both in services and functions as they play host to carbon sinks, fishery breeding grounds and natural coastal barriers against storms. In addition to the globally important biodiversity that they contain, they also contribute to local livelihoods. Despite these appraisals, a reduction of about 30 % over a 25 years period due to anthropogenic and natural actions has been recorded. The key drivers influencing mangrove change include population growth, climate change, economic and political trends and upstream habitat use. Reversing the trend of mangrove loss and growing vulnerability of coastal peoples requires a real commitment by the government to develop and implement robust level policies. It has been observed in Cameroon that special ecosystems like mangroves are insufficiently addressed by forestry and/or environment programs. Given these facts, the Food Agriculture Organization (FAO) in partnership with the Government of Cameroon and other development actors have put in place the project for sustainable community-based management and conservation of mangrove ecosystems in Cameroon. The aim is to address two issues notably the present weak institutional and legal framework for mangrove management, and the unrestricted and unsustainable harvesting of mangrove resources. Civil society organizations like the Cameroon Wildlife Conservation Society, Cameroon Ecology and Organization for the Environment and Development have been working to reduce the deforestation and degradation trend of Cameroon mangroves and also bringing the mangrove agenda to the fore in national and international arenas. Following a desktop approach, we found out that in situ and ex situ initiatives on mangrove management and conservation exist on propagation of improved fish smoke ovens to reduce fuel wood consumption, mangrove forest regeneration, shrimps farming and mangrove protected areas management. The evidence generated from the field experiences are inputs for processes of improving the legal and institutional framework for mangrove management in Cameroon, such as the elaboration of norms for mangroves management engaged by the government.

Keywords: mangrove ecosystem, legal and institutional framework, climate change, civil society organizations

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Authors: Alvaro Javier Ortega

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A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

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Authors: Juliza Hidayati, Sukardi, Ani Suryani, Sugiharto, Anas M. Fauzi

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The idea of making North Sumatera as a barometer of national oil palm industry requires efforts commodities and agro-industry development of oil palm. One effort that can be done is by successful execution plantation revitalization. The plantation Revitalization is an effort to accelerate the development of smallholder plantations, through expansion and replanting by help of palm Estate Company as business partner and bank financed plantation revitalization fund. Business partner agreement obliged and bound to make at least the same smallholder plantation productivity with business partners, so that the refund rate to banks become larger and prosperous people as a plantation owner. Generally low productivity of smallholder plantations under normal potential caused a lot of old and damaged plants with plant material at random. The purpose of revitalizing oil palm plantations is which are to increase their competitiveness through increased farm productivity. The research aims to identify potential criteria in influencing plantation productivity improvement priorities to be observed and followed up in order to improve the competitiveness of destinations and make North Sumatera barometer of national palm oil can be achieved. Research conducted with Analytical Network Process (ANP), to find the effect of dependency relationships between factors or criteria with the knowledge of the experts in order to produce an objective opinion and relevant depict the actual situation.

Keywords: palm barometer, acceleration of plantation development, productivity, revitalization

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Authors: Onyinyechi Joy Kingdom

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Mergers and Acquisitions (M&A) have been proposed as a mechanism through which, problems associated with inefficiency or poor performance in financial institution could be addressed. The aim of this study is to examine the proposition that recapitalization of banks, which encouraged Mergers and Acquisitions in Nigeria banking system, would strengthen the domestic banks, improve financial deepening and the confidence of depositors. Hence, this study examines the impact of the 2005 M&A in the Nigerian-banking sector on financial deepening using mixed method (quantitative and qualitative approach). The quantitative process of this study utilised annual time series for financial deepening indicator for the period of 1997 to 2012. While, the qualitative aspect adopted semi-structured interview to collate data from three merged banks and three stand-alone banks to explore, understand and complement the quantitative results. Furthermore, a framework thematic analysis is employed to analyse the themes developed using NVivo 11 software. Using the quantitative approach, findings from the equality of mean test (EMT) used suggests that M&A have significant impact on financial deepening. However, this method is not robust enough given its weak validity as it does not control for other potential factors that may determine financial deepening. Thus, to control for other factors that may affect the level of financial deepening, a Multiple Regression Model (MRM) and Interrupted Times Series Analysis (ITSA) were applied. The coefficient for M&A dummy turned negative and insignificant using MRM. In addition, the estimated linear trend of the post intervention when ITSA was applied suggests that after M&A, the level of financial deepening decreased annually; however, this was statistically insignificant. Similarly, using the qualitative approach, the results from the interview supported the quantitative results from ITSA and MRM. The result suggests that interest rate should fall when capital base is increased to improve financial deepening. Hence, this study contributes to the existing literature the importance of other factors that may affect financial deepening and the economy when policies that will enhance bank performance and the economy are made. In addition, this study will enable the use of valuable policy instruments relevant to monetary authorities when formulating policies that will strengthen the Nigerian banking sector and the economy.

Keywords: mergers and acquisitions, recapitalization, financial deepening, efficiency, financial crisis

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Authors: Areej Isam Barham

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The implementation of Japanese lesson study approach in the mathematics classroom has been grown worldwide as a model of professional development for teachers. In Qatar, the implementation of IMPULS-QU lesson study program aimed to establish a robust organizational improvement model of professional development for mathematics teachers in Qatar schools. This study describes the implementation of a lesson study model at Al-Markhyia Independent Primary School through different stages; and discusses how the planning process, the research lesson, and the post discussion participates in providing teachers and researchers with a successful research lesson for teacher professional development. The research followed a case study approach in one mathematics classroom. Two teachers and one professional development specialist participated the planning process. One teacher conducted the research lesson study by introducing a problem solving related to the concept of the ‘Mean’ in a mathematics class, 21 students in grade 6 participated in solving the mathematic problem, 11 teachers, 4 professional development specialists, and 4 mathematics professors observed the research lesson. All previous participants except the students participated in a pre and post-lesson discussion within this research. This study followed a qualitative research approach by analyzing the collected data through different stages in the research lesson study. Observation, field notes, and semi-structured interviews conducted to collect data to achieve the research aims. One feature of this lesson study research is that this research describes the implementation for a lesson study as a new experience for one mathematics teacher and 21 students after 3 years of conducting IMPULS-QU project in Al-Markhyia school. The research describes various stages through the implementation of this lesson study model starting from the planning process and ending by the post discussion process. Findings of the study also address the impact of lesson study approach in teaching mathematics for the development of teachers from their point views. Results of the study show the benefits of using lesson study from the point views of participated teachers, theory perceptions about the essential features of lesson study, and their needs for future development. The discussion of the study addresses different features and issues related to the implementation of IMPULS-QU lesson study model in the mathematics classroom. In the light of the study, the research presents recommendations and suggestions for future professional development.

Keywords: lesson study, mathematics education, mathematics teaching experience, teacher professional development

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Authors: Bencheikh Messaouda, Aidoud Assia, Salima Boukour, Benamara Fatima Zohra, Boukhatem Ghania, Zegueur Chaouki Salah Eddine

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The utilization of waste materials in civil engineering has gained widespread attention in recent years due to their adverse effects on the environment. One such waste material is coffee grounds, a black residue generated daily across the country after coffee brewing. Instead of disposing of it, there is a growing interest in repurposing it for various agricultural and industrial applications. Utilizing coffee grounds in geotechnical engineering, such as in road embankments, presents an opportunity for its valorization. The study aims to contribute to the valorization of coffee grounds by enhancing the physical and mechanical properties of clayey soils through their incorporation at varying weight percentages (3%, 6%, 9%, 12%) as partial replacements in these soils. This not only addresses the issue of coffee ground waste but also makes a tangible contribution to sustainable development. The findings demonstrate that incorporating coffee grounds generally has positive effects on the physical and mechanical properties of clayey soil. However, the extent of these effects depends on factors such as the quantity of coffee grounds added, the particle size of the grounds, and the characteristics of the soil. Additionally, coffee grounds can improve the compression and tensile strength of clayey soil, resulting in increased stability and reduced susceptibility to deformation under external forces.

Keywords: clay soil, coffee grounds, optimizing, improvement, valorization, waste

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Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts

Procedia PDF Downloads 118

Authors: Feleke Tsegaye

Abstract:

The work in this thesis mainly focuses on trajectory tracking of fixed wing unmanned aerial vehicle (FWUAV) by using fuzzy based sliding mode controller(FSMC) for surveillance applications. Unmanned Aerial Vehicles (UAVs) are general-purpose aircraft built to fly autonomously. This technology is applied in a variety of sectors, including the military, to improve defense, surveillance, and logistics. The model of FWUAV is complex due to its high non-linearity and coupling effect. In this thesis, input decoupling is done through extracting the dominant inputs during the design of the controller and considering the remaining inputs as uncertainty. The proper and steady flight maneuvering of UAVs under uncertain and unstable circumstances is the most critical problem for researchers studying UAVs. A FSMC technique was suggested to tackle the complexity of FWUAV systems. The trajectory tracking control algorithm primarily uses the sliding-mode (SM) variable structure control method to address the system’s control issue. In the SM control, a fuzzy logic control(FLC) algorithm is utilized in place of the discontinuous phase of the SM controller to reduce the chattering impact. In the reaching and sliding stages of SM control, Lyapunov theory is used to assure finite-time convergence. A comparison between the conventional SM controller and the suggested controller is done in relation to the chattering effect as well as tracking performance. It is evident that the chattering is effectively reduced, the suggested controller provides a quick response with a minimum steady-state error, and the controller is robust in the face of unknown disturbances. The designed control strategy is simulated with the nonlinear model of FWUAV using the MATLAB® / Simulink® environments. The simulation result shows the suggested controller operates effectively, maintains an aircraft’s stability, and will hold the aircraft’s targeted flight path despite the presence of uncertainty and disturbances.

Keywords: fixed-wing UAVs, sliding mode controller, fuzzy logic controller, chattering, coupling effect, surveillance, finite-time convergence, Lyapunov theory, flight path

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

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The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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Authors: Brennan Lodge

Abstract:

Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

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Authors: Mahdi GoharRokhi, Mohammad H. Ruhipour, Mohammad R. ZamaniZadeh, Mohsen Maleki, Yusef Shamsayi, Mahdi FarhaniNejad, Farzad FarrokhZadeh

Abstract:

Possessing massive resources of natural gas and petroleum, Iran has a special place among all other oil producing countries, according to international institutions of energy. In order to use these resources, development and functioning optimization of refineries and industrial units is mandatory. Heat exchanger is one of the most important and strategic equipment which its key role in the process of production is clear to everyone. For instance, if the temperature of a processing fluid is not set as needed by heat exchangers, the specifications of desired product can change profoundly. Crude oil enters a network of heat exchangers in atmospheric distillation section before getting into the distillation tower; in this case, well-functioning of heat exchangers can significantly affect the operation of distillation tower. In this paper, different scenarios for pre-heating of oil are studied using oil and gas simulation software, and the results are discussed. As we reviewed various scenarios, adding a heat exchanger to pre-heating network is proposed as the most efficient factor in improving all governing parameters of the tower i.e. temperature, pressure, and reflux rate. This exchanger is embedded in crude oil’s path. Crude oil enters the exchanger after E-101 and exchanges heat with discharging kerosene pump around from E-136. As depicted in the results, it will efficiently assist the improvement of process operation and side expenses.

Keywords: atmospheric distillation unit, heat exchanger, preheat, simulation

Procedia PDF Downloads 635