Search results for: finite element model/COMSOL multiphysics

Authors: RAJ KUMAR G.C.

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There are tremendous opportunities to maximize smallholder farmers’ income from small-scale water resource development through micro irrigation and multiple-use water systems (MUS). MUS are an improved water management approach, developed and tested successfully by iDE that pipes water to a community both for domestic use and for agriculture using efficient micro irrigation. Different MUS models address different landscape constraints, water demand, and users’ preferences. MUS are complemented by micro irrigation kits, which were developed by iDE to enable farmers to grow high-value crops year-round and to use limited water resources efficiently. Over the last 15 years, iDE’s promotion of the MUS approach has encouraged government and other key stakeholders to invest in MUS for better planning of scarce water resources. Currently, about 60% of the cost of MUS construction is covered by the government and community. Based on iDE’s experience, a gravity-fed MUS costs approximately $125 USD per household to construct, and it can increase household income by $300 USD per year. A key element of the MUS approach is keeping farmers well linked to input supply systems and local produce collection centers, which helps to ensure that the farmers can produce a sufficient quantity of high-quality produce that earns a fair price. This process in turn creates an enabling environment for smallholders to invest in MUS and micro irrigation. Therefore, MUS should be seen as an integrated package of interventions –the end users, water sources, technologies, and the marketplace– that together enhance technical, financial, and institutional sustainability. Communities are trained to participate in sustainable water resource management as a part of the MUS planning and construction process. The MUS approach is cost-effective, improves community governance of scarce water resources, helps smallholder farmers to improve rural health and livelihoods, and promotes gender equity. MUS systems are simple to maintain and communities are trained to ensure that they can undertake minor maintenance procedures themselves. All in all, the iDE Nepal MUS offers multiple benefits and represents a practical and sustainable model of the MUS approach. Moreover, there is a growing national consensus that rural water supply systems should be designed for multiple uses, acknowledging that substantial work remains in developing national-level and local capacity and policies for scale-up.

Keywords: multiple-use water systems , small scale water resources, rural livelihoods, practical and sustainable model

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Authors: Kai Jin, Hua Li, Qing Song

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Homeland security and border safety is an issue for any country. This paper takes the border security of US as an example to discuss the usage and efficiency of simulation tools in the homeland security application. In this study, available resources and different illegal infiltration parameters are defined, including their individual behavior and objective, in order to develop a model that describes border patrol system. A simulation model is created in Arena. This simulation model is used to study the dynamic activities in the border security. Possible factors that may affect the effectiveness of the border patrol system are proposed. Individual and factorial analysis of these factors is conducted and some suggestions are made.

Keywords: resource optimization, simulation, modeling, border security

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Mohamed Abd Esselem Dems, Souhila Laib, Nadjia Latelli, Nadia Ouddai

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In this work, we have developed QSAR model for Relative Binding Affinity (RBA) of a large diverse set of estradiol among these derivatives, the organometallic derivatives. By dividing the dataset into a training set of 24 compounds and a test set of 6 compounds. The DFT method was used to calculate quantum chemical descriptors and physicochemical descriptors (MR and MLOGP) were performed using E-Dragon. All the validations indicated that the QSAR model built was robust and satisfactory (R2 = 90.12, Q2LOO = 86.61, RMSE = 0.272, F = 60.6473, Q2ext =86.07). We have therefore apply this model to predict the RBA, for two isomers β and α wherein Mn(CO)3 complex with the aromatic ring of estradiol, and the two isomers show little appreciation for the estrogenic receptor (RBAβ = 1.812 and RBAα = 1.741).

Keywords: DFT, estradiol, haptotropic rearrangement, QSAR, relative binding affinity

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Authors: Elina Bakhtieva

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The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis

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Authors: Seyed M. Khatami, H. Naderpour, R. Vahdani, R. C. Barros

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Many previous studies have been carried out to calculate the impact force and the dissipated energy between two neighboring buildings during seismic excitation, when they collide with each other. Numerical studies are an important part of impact, which several researchers have tried to simulate the impact by using different formulas. Estimation of the impact force and the dissipated energy depends significantly on some parameters of impact. Mass of bodies, stiffness of spring, coefficient of restitution, damping ratio of dashpot and impact velocity are some known and unknown parameters to simulate the impact and measure dissipated energy during collision. Collision is usually shown by force-displacement hysteresis curve. The enclosed area of the hysteresis loop explains the dissipated energy during impact. In this paper, the effect of using different types of impact models is investigated in order to calculate the impact force. To increase the accuracy of impact model and to optimize the results of simulations, a new damping equation is assumed and is validated to get the best results of impact force and dissipated energy, which can show the accuracy of suggested equation of motion in comparison with other formulas. This relation is called "n-m". Based on mathematical relation, an initial value is selected for the mentioned coefficients and kinetic energy loss is calculated. After each simulation, kinetic energy loss and energy dissipation are compared with each other. If they are equal, selected parameters are true and, if not, the constant of parameters are modified and a new analysis is performed. Finally, two unknown parameters are suggested to estimate the impact force and calculate the dissipated energy.

Keywords: impact force, dissipated energy, kinetic energy loss, damping relation

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Prakash Kumar Nayak, Avinash Kumar, Uma Dash, Kalpana Rayaguru

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Soybean oil is one of the most widely consumed cooking oils, worldwide. Deep-fat frying of foods at higher temperatures adds unique flavour, golden brown colour and crispy texture to foods. But it brings in various changes like hydrolysis, oxidation, hydrogenation and thermal alteration to oil. The presence of Peroxide value (PV) is one of the most important factors affecting the quality of the deep-fat fried oil. Using bentonite as an adsorbent, the PV can be reduced, thereby improving the quality of the soybean oil. In this study, operating parameters like heating time of oil (10, 15, 20, 25 & 30 h), contact time ( 5, 10, 15, 20, 25 h) and concentration of adsorbent (0.25, 0.5, 0.75, 1.0 and 1.25 g/ 100 ml of oil) have been optimized by response surface methodology (RSM) considering percentage reduction of PV as a response. Adsorption data were analysed by fitting with Langmuir and Freundlich isotherm model. The results show that the Langmuir model shows the best fit compared to the Freundlich model. The adsorption process was also found to follow a pseudo-second-order kinetic model.

Keywords: bentonite, Langmuir isotherm, peroxide value, RSM, soybean oil

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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Authors: E. Nakamachi, S. Tanaka, K. Yamamoto, Y. Morita

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In this study, we developed a three-dimensional (3D) direct current electric field (DCEF) stimulation bio-reactor for axonal outgrowth enhancement to generate the neural network of the central nervous system (CNS). By using our newly developed 3D DCEF stimulation bio-reactor, we cultured the rat pheochromocytoma cells (PC12) and investigated the effects on the axonal extension enhancement and network generation. Firstly, we designed and fabricated a 3D bio-reactor, which can load DCEF stimulation on PC12 cells embedded in the collagen gel as extracellular environment. The connection between the electrolyte and the medium using salt bridges for DCEF stimulation was introduced to avoid the cell death by the toxicity of metal ion. The distance between the salt bridges was adopted as the design variable to optimize a structure for uniform DCEF stimulation, where the finite element (FE) analyses results were used. Uniform DCEF strength and electric flux vector direction in the PC12 cells embedded in collagen gel were examined through measurements of the fabricated 3D bio-reactor chamber. Measurement results of DCEF strength in the bio-reactor showed a good agreement with FE results. In addition, the perfusion system was attached to maintain pH 7.2 ~ 7.6 of the medium because pH change was caused by DCEF stimulation loading. Secondly, we disseminated PC12 cells in collagen gel and carried out 3D culture. Finally, we measured the morphology of PC12 cell bodies and neurites by the multiphoton excitation fluorescence microscope (MPM). The effectiveness of DCEF stimulation to enhance the axonal outgrowth and the neural network generation was investigated. We confirmed that both an increase of mean axonal length and axogenesis rate of PC12, which have been exposed 5 mV/mm for 6 hours a day for 4 days in the bioreactor. We found following conclusions in our study. 1) Design and fabrication of DCEF stimulation bio-reactor capable of 3D culture nerve cell were completed. A uniform electric field strength of average value of 17 mV/mm within the 1.2% error range was confirmed by using FE analyses, after the structure determination through the optimization process. In addition, we attached a perfusion system capable of suppressing the pH change of the culture solution due to DCEF stimulation loading. 2) Evaluation of DCEF stimulation effects on PC12 cell activity was executed. The 3D culture of PC 12 was carried out adopting the embedding culture method using collagen gel as a scaffold for four days under the condition of 5.0 mV/mm and 10mV/mm. There was a significant effect on the enhancement of axonal extension, as 11.3% increase in an average length, and the increase of axogenesis rate. On the other hand, no effects on the orientation of axon against the DCEF flux direction was observed. Further, the network generation was enhanced to connect longer distance between the target neighbor cells by DCEF stimulation.

Keywords: PC12, DCEF stimulation, 3D bio-reactor, axonal extension, neural network generation

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Authors: Rizwan Arshad, Alessio Panza, Nimra Inayat, Syeda Mariam Batool Kazmi, Shawana Azmat

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The rapidly expanding use of immunotherapy for a wide range of cancers from late to early stages has, predictably, been accompanied by evidence of inequities in access to these highly effective but costly treatments. In this survey-based case study, we aimed to develop a One-window services model (OWSM) based on Anderson’s behavioral model to enhance competence in accessing cancer medications, particularly immunotherapies, through the analysis of 20 patient surveys conducted in the Armed forces bone marrow transplant center of the district, Rawalpindi from November to December 2022. The purposive sampling technique was used. Cronbach’s alpha coefficient was found to be 0.71. It was analyzed using SPSS version 26 with descriptive analysis, and results showed that the majority of the cancer patients were non-competent to access their prescribed cancer immunotherapy because of individual-level, socioeconomic, and organizational barriers.

Keywords: cancer immunotherapy, one-window services model, accessibility, competence

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Authors: Ivelise M. Strozberg, Lucas O. Vale, Maria V. V. Morais

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Expansive soils are characterized by their significant volumetric variations, tending to suffer an increase of this volume when added water in their voids and a decrease of volume when this water is removed. The parameters of resistance (especially the angle of friction, cohesion and specific weight) of expansive or non-expansive soils of the same field present differences, as found in laboratory tests. What is expected is that, through this research, demonstrate that this variation directly affects the results of the calculation of factors of safety for slope stability. The expansibility due to specific clay minerals such as montmorillonites and vermiculites is the most common form of expansion of soils or rocks, causing expansion pressures. These pressures can become an aggravating problem in regions across the globe that, when not previously studied, may present high risks to the enterprise, such as cracks, fissures, movements in structures, breaking of retaining walls, drilling of wells, among others. The study provides results based on analyzes carried out in the Slide 2018 software belonging to the Rocsience group, where the software is a two-dimensional equilibrium slope stability program that calculates the factor of safety or probability of failure of certain surfaces composed of soils or rocks (or both, depending on the situation), - through the methods of: Bishop simplified, Fellenius and Janbu corrected. This research compares the factors of safety of a homogeneous earthfill dam geometry, analysed for operation and end-of-construction situations, having a height of approximately 35 meters, with a slope of 1.5: 1 in the slope downstream and 2: 1 on the upstream slope. As the water level is 32.73m high and the water table is drawn automatically by the Slide program using the finite element method for the operating situation, considering two hypotheses for the use of materials - the first with soils with characteristics of expansion and the second with soils without expansibility. For this purpose, soil samples were collected from the region of São Bento do Una - Pernambuco, Brazil and taken to the soil mechanics laboratory to characterize and determine the percentage of expansibility. There were found 2 types of soils in that area: 1 site of expansive soils (8%) and another with non- expansive ones. Based on the results found, the analysis of the values of factors of safety indicated, both upstream and downstream slopes, the highest values were obtained in the case where there is no presence of materials with expansibility resulting, for one of the situations, values of 1.353 (Fellenius), 1,295 (Janbu corrected) and 1,409 (Bishop simplified). There is a considerable drop in safety factors in cases where soils are potentially expansive, resulting in values for the same situation of 0.859 (Fellenius), 0.809 (Janbu corrected) and 0.842 (Bishop simplified), in the case of higher expansibility (8 %). This shows that the expansibility is a determinant factor in the fall of resistance of soil, determined by the factors of cohesion and angle of friction.

Keywords: dam. slope. software. swelling soil

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Authors: Seyedsamad Tahani, Samira Ghorbanpour

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The global warming crisis forced humans to consider their place in the world and the earth's future. In this regard, Electric Vehicles (EVs) are a significant step toward protecting the environment. By identifying factors that influence people's behavior intentions toward using Electric Vehicles (EV), we proposed a theoretical model by extending the Technology Acceptance Model (TAM), including three more concepts, Subjective Norm (SN), Self-Efficacy (SE), and Perceived Behavior Control (PBC). The study was conducted in South Korea, and a random sample was taken at a specific time. In order to collect data, a questionnaire was created in a Google Form and sent via Kakao Talk, a popular social media application used in Korea. There were about 220 participants in this survey. However, 201 surveys were completely done. The findings revealed that all factors in the TAM model and the other added concepts such as subjective norms, self-efficacy and perceived behavior control significantly affect the behavioral intention of using EVs.

Keywords: electric vehicles, behavioral intention, perceived trust, perceived enjoyment, self-efficacy

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Authors: Jia Li, Huacong Li, Xiaobao Han

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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

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Authors: Hamza Hafidi Alaoui, Damien Leduc, Mounsif Ech Cherif El Kettani

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This study is dedicated to the evaluation of the ageing of turbine blades in sea conditions, based on ultrasonic Non Destructive Testing (NDT) methods. This study is being developed within the framework of the European Interreg TIGER project. The Tidal Stream Industry Energiser Project, known as TIGER, is the biggest ever Interreg project driving collaboration and cost reductionthrough tidal turbine installations in the UK and France. The TIGER project will drive the growth of tidal stream energy to become a greater part of the energy mix, with significant benefits for coastal communities. In the bay of Paimpol-Bréhat (Brittany), different samples of composite material and bonded composite/composite structures have been immersed at the same time near a turbine. The studied samples are either conventional carbon-epoxy composite samples or composite samples based on a recyclable resin (called recyclamine). One of the objectives of the study is to compare the ageing of the two types of structure. A sample of each structure is picked up every 3 to 6 months and analyzed using ultrasonic guided waves and bulk waves and compared to reference samples. In order to classify the damage level as a function of time spent under the sea, the measure have been compared to a rheological model based on the Finite Elements Method (FEM). Ageing of the composite material, as well as that of the adhesive, is identified. The aim is to improve the quality of the turbine blade structure in terms of longevity and reduced maintenance needs.

Keywords: non-destructive testing, ultrasound, composites, guides waves

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: A. Kumar, V. Devadas

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Energy is the basic element for any country’s economic development. India is one of the most populated countries, and is dependent on fossil fuel and nuclear-based energy generation. The energy sector faces huge challenges and is dependent on the import of energy from neighboring countries to fulfill the gap in demand and supply. India has huge setbacks for efficient energy generation, distribution, and consumption, therefore they consume more quantity of energy to produce the same amount of Gross Domestic Product (GDP) compared to the developed countries. Technology and technique use, availability, and affordability in the various sectors are varying according to their economic status. In this paper, an attempt is made to quantify the domestic electrical energy consumption in Jodhpur, India. Survey research methods have been employed and stratified sampling technique-based households were chosen for conducting the investigation. Pre-tested survey schedules are used to investigate the grassroots level study. The collected data are analyzed by employing statistical techniques. Thereafter, a multiple regression model is developed to understand the functions of total electricity consumption in the domestic sector corresponding to other independent variables including electrical appliances, age of the building, household size, education, etc. The study resulted in identifying the governing variable in energy consumption at the household level and their relationship with the efficiency of household-based electrical and energy appliances. The analysis is concluded with the recommendation for optimizing the gap in peak electrical demand and supply in the domestic sector.

Keywords: appliance, consumption, electricity, households

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Authors: Morenike Abimbola Adeleye, Anthony Temidayo Bolarinwa

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The genesis of talc bodies around Wonu, Ibadan-Apomu area, southwestern Nigeria, has been speculative due to inadequate compositional data on the talc and the mafic-ultramafic protoliths. Petrography, morphology, using scanning electron microscope, mineral chemistry, X-ray diffraction, and major, trace and rare-earth element compositions of the talc and the mafic-ultramafic in the area were undertaken with a view to determine the genesis of the talc bodies. Fine-grained amphibolite and lherzolite are the major mafic-ultramafic rocks in the study area. The amphibolite is fine-grained, composed of amphiboles, pyroxenes plagioclase, K-feldspar, ilmenite, magnetite, and garnet. The lherzolite and talc are composed of olivines, pyroxenes, amphiboles, and plagioclase. Alteration minerals include serpentine, amesite, talc, Cr-bearing clinochlore, and ferritchromite. Cr-spinel, pyrite, and magnetite are the accessory minerals present. Alteration of olivines, pyroxenes, and amphiboles to talc and chlinochlore; and spinel to ferritchchromite by hydrothermal (H₂O-CO₂-Cl-HF) fluids, provided by the granitic intrusions in the area, showed retrograde metasomatism of amphibolites to greenschist facies at 500-550ºC. This led to the formation of talc, amesite, anthophyllite, actinolite, and tremolite. The Al₂O₃-Fe₂O₃+TiO₂-MgO discrimination diagram suggests tholeiitic protolith for the amphibolite and komatitic protolith for the lherzolite. The lherzolite has flat rare-earth element patterns typical of komatiites and dunites. The Al₂O₃/TiO₂ ratios, Ce/Nb vs. Th/Nb, Cr-TiO₂, TiO₂ vs. Al₂O₃, and Nd vs. Nb discrimination diagrams indicated that the talcs are from two-parent sources: altered metacarbonates and tholeiitic basalts (amphibolites) to komatitic basalts (lherzolites).

Keywords: amphibolites, lherzolites, talc, komatiite

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Authors: Marcelo Hayashi, João Lima, Bruno Chieregatti, Ernani Volpe

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The adjoint method has been used as a successful tool to obtain sensitivity gradients in aerodynamic design and optimisation for many years. This work presents an alternative approach to the continuous adjoint formulation that enables one to compute gradients of a given measure of merit with respect to control parameters other than those pertaining to geometry. The procedure is then applied to the steady 2–D compressible Euler and incompressible Navier–Stokes flow equations. Finally, the results are compared with sensitivities obtained by finite differences and theoretical values for validation.

Keywords: adjoint method, aerodynamics, sensitivity theory, non-geometric sensitivities

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Authors: Probir Kumar Banerjee

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Though the revised DeLone and McLean (DM) model of IS success is found to be effective at the individual level of analysis, there is lack of consensus in regard to its effectiveness at the organisational level. This research reviews the DM model in the light of business/IT alignment theory and supporting literature, and suggests its reconceptualization. Specifically, arguments are made for augmenting it with business process quality. Business process quality, it is argued, captures the effect of intent to use, use and user satisfaction interactions, thus eliminating the need to capture their interaction effects in explaining organisational IS success. It is also argued that ‘operational performance’ driven by systems and business process quality, and higher order measures of organisational performance tied to operational performance are appropriate measures of ‘net benefit’. Suggestions are made for reconceptualisation of the other constructs and an adapted model of organisational IS success is proposed.

Keywords: organisational IS success, business/IT alignment, systems quality, business process quality, operational performance, market performance

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Authors: Settapong Malisuwan, Jesada Sivaraks, Peerawat Promkladpanao, Nattakit Suriyakrai, Navneet Madan

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In this paper, a compact microstrip patch antenna is designed for mobile LTE applications by applying the frequency-dependent Smith-Chart (FDSC) model. The FDSC model is adopted in this research to reduce the error on the frequency-dependent characteristics. The Ansoft HFSS and various techniques is applied to meet frequency and size requirements. The proposed method within this research is suitable for use in computer-aided microstrip antenna design and RF integrated circuit (RFIC) design.

Keywords: frequency-dependent, smith-chart, microstrip, antenna, LTE, CAD

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Authors: Sajjad Baghernezhad

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Meta-heuristic and hybrid algorithms have high adeer in modeling medical problems. In this study, a neural network was used to predict covid-19 among high-risk and low-risk patients. This study was conducted to collect the applied method and its target population consisting of 550 high-risk and low-risk patients from the Kerman University of medical sciences medical center to predict the coronavirus. In this study, the memetic algorithm, which is a combination of a genetic algorithm and a local search algorithm, has been used to update the weights of the neural network and develop the accuracy of the neural network. The initial study showed that the accuracy of the neural network was 88%. After updating the weights, the memetic algorithm increased by 93%. For the proposed model, sensitivity, specificity, positive predictivity value, value/accuracy to 97.4, 92.3, 95.8, 96.2, and 0.918, respectively; for the genetic algorithm model, 87.05, 9.20 7, 89.45, 97.30 and 0.967 and for logistic regression model were 87.40, 95.20, 93.79, 0.87 and 0.916. Based on the findings of this study, neural network models have a lower error rate in the diagnosis of patients based on individual variables and vital signs compared to the regression model. The findings of this study can help planners and health care providers in signing programs and early diagnosis of COVID-19 or Corona.

Keywords: COVID-19, decision support technique, neural network, genetic algorithm, memetic algorithm

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Authors: Rumeysa Terzioglu

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Social entrepreneurship is not only a new concept but also an engaging factor of development that utilizes opportunities in economic and social areas for women. Social entrepreneurs have experience in determining and solving social problems with community participation. Social entrepreneurship is a consequence of individual social and economic initiatives contributing to women’s social and economic development against poverty. Women’s empowerment is an essential point for development. Türkiye has been developing an alternative empowerment model for women affected by the national development plan. Social entrepreneurship is an alternative model of social and economic empowerment of women’s status in Türkiye.

Keywords: social entrepreneurship, women, women empowerment, development

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Authors: Zhuang Guo

Abstract:

In the field of GaN-based resonant tunneling diodes (RTDs) simulations, the traditional Tsu-Esaki formalism failed to predict the values of peak currents and peak voltages in the simulated current-voltage(J-V) characteristics. The main reason is that due to the strong internal polarization fields, two-dimensional electron gas(2DEG) accumulates at emitters, resulting in 2D-2D resonant tunneling currents, which become the dominant parts of the total J-V characteristics. By comparison, based on the 3D-2D resonant tunneling mechanism, the traditional Tsu-Esaki formalism cannot predict the J-V characteristics correctly. To overcome this shortcoming, we develop a new analytical model for the 2D-2D resonant tunneling currents generated in GaN-based RTDs. Compared with Tsu-Esaki formalism, the new model has made the following modifications: Firstly, considering the Heisenberg uncertainty, the new model corrects the expression of the density of states around the 2DEG eigenenergy levels at emitters so that it could predict the half width at half-maximum(HWHM) of resonant tunneling currents; Secondly, taking into account the effect of bias on wave vectors on the collectors, the new model modifies the expression of the transmission coefficients which could help to get the values of peak currents closer to the experiment data compared with Tsu-Esaki formalism. The new analytical model successfully predicts the J-V characteristics of GaN-based RTDs, and it also reveals more detailed mechanisms of resonant tunneling happened in GaN-based RTDs, which helps to design and fabricate high-performance GaN RTDs.

Keywords: GaN-based resonant tunneling diodes, tsu-esaki formalism, 2D-2D resonant tunneling, heisenberg uncertainty

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Authors: Hyun Joon Chang, Jae In Kim, Sungsoo Na

Abstract:

Kinesin-1 (hereafter called kinesin) is a molecular motor protein that moves cargos toward the end of microtubules using the energy of adenosine triphosphate (ATP) hydrolysis. When kinesin is inactive, its tail autoinhibits the motor chain in order to prevent from reacting with the ATP by cross-linking of the tail domain to the motor domains at two positions. However, the morphological study of kinesin during autoinhibition is yet remained obscured. In this study, we report the effect of the binding site of the tail domain using the normal mode analysis of the elastic network model on kinesin in the tail-free form and tail-bind form. Considering the relationship between the connectivity of conventional network model with respect to the cutoff length and the functionality of the binding site of the tail, we revaluated the network model to observe the key role of the tail domain in its structural aspect. Contingent on the existence of the tail domain, the results suggest the morphological stability of the motor domain. Furthermore, employing the results from normal mode analysis, we have determined the strain energy of the neck linker, an essential portion of the motor domain for ATP hydrolysis. The results of the neck linker also converge to the same indication, i.e. the morphological analysis of the motor domain.

Keywords: elastic network model, Kinesin-1, autoinhibition

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Authors: Slim Amami

Abstract:

A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, database, meteorological factors, production model, optimal price

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Authors: Lailial Muhtifah, Sirtul Marhamah

Abstract:

This article forwards the conceptual framework of continuous academic lecturer model in Islamic higher education (IHE). It is intended to make a contribution to the broader issue of how the concept of excellence can promote adherence to standards in higher education and drive quality enhancement. This model reveals a process and steps to increase performance and achievement of excellence regular lecturer gradually. Studies in this model are very significant to realize excellence academic culture in IHE. Several steps were identified from previous studies through literature study and empirical findings. A qualitative study was conducted at institute. Administrators and lecturers were interviewed, and lecturers learning communities observed to explore institute culture policies, and procedures. The original in this study presents and called Continuous Academic Lecturer Model (CALM) with its components, namely Standard, Quality, and Excellent as the basis for this framework (SQE). Innovation Excellence Framework requires Leaders to Support (LS) lecturers to achieve a excellence culture. So, the model named CALM-SQE+LS. Several components of performance and achievement of CALM-SQE+LS Model should be disseminated and cultivated to all lecturers in university excellence in terms of innovation. The purpose of this article is to define the concept of “CALM-SQE+LS”. Originally, there were three components in the Continuous Academic Lecturer Model i.e. standard, quality, and excellence plus leader support. This study is important to the community as specific cases that may inform educational leaders on mechanisms that may be leveraged to ensure successful implementation of policies and procedures outline of CALM with its components (SQE+LS) in institutional culture and professional leader literature. The findings of this study learn how continuous academic lecturer is part of a group's culture, how it benefits in university. This article blends the available criteria into several sub-component to give new insights towards empowering lecturer the innovation excellence at the IHE. The proposed conceptual framework is also presented.

Keywords: continuous academic lecturer model, excellence, quality, standard

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Authors: Hidouri Sami, Aguili Taoufik

Abstract:

We consider fast and accurate solutions of scattering problems by large perfectly conducting objects (PEC) formulated by an optimization of the Method of Auxiliary Sources (MAS). We present various techniques used to reduce the total computational cost of the scattering problem. The first technique is based on replacing the object by an array of finite number of small (PEC) object with the same shape. The second solution reduces the problem on considering only the half of the object.These two solutions are compared to results from the reference bibliography.

Keywords: method of auxiliary sources, scattering, large object, RCS, computational resources

Procedia PDF Downloads 245