Search results for: overall equipment effectiveness

Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: Yufeng Wu, Yifan Gu, Bin Li, Wei Wang

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Resource recycling process contains a subsystem with interactions of three dimensions including coupling allocation of primary and secondary resources, responsibility coordination of stakeholders in forward and reverse supply chains, and trans-boundary transfer of hidden resource and environmental responsibilities between regions. Overlap or lack of responsibilities is easy to appear at the intersection of the three management dimensions. It is urgent to make an overall design of the policy system for recycling resources. From theoretical perspective, this paper analyzes the unique external differences of resource and environment in various dimensions and explores the reason why the effects of trans-dimensional policies are strongly correlated. Taking the example of the copper resources contained in the waste electrical and electronic equipment, this paper constructs reduction effect accounting model of resources recycling and set four trans-dimensional policy scenarios including resources tax and environmental tax reform of the raw and secondary resources, application of extended producer responsibility system, promotion of clean development mechanism, and strict entry barriers of imported wastes. In these ways, the paper simulates the impact effect of resources recycling process on resource deduction and emission reduction of waste water and gas, and constructs trans-dimensional policy mix scenario through integrating dominant strategy. The results show that combined application of various dimensional policies can achieve incentive compatibility and the trans-dimensional policy mix scenario can reach a better effect. Compared with baseline scenario, this scenario will increase 91.06% copper resources reduction effect and improve emission reduction of waste water and gas by eight times from 2010 to 2030. This paper further analyzes the development orientation of policies in various dimension. In resource dimension, the combined application of compulsory, market and authentication methods should be promoted to improve the use ratio of secondary resources. In supply chain dimension, resource value, residual functional value and potential information value contained in waste products should be fully excavated to construct a circular business system. In regional dimension, it should give full play to the comparative advantages of manufacturing power to improve China’s voice in resource recycling in the world.

Keywords: resource recycling, trans-dimension, policy design, incentive compatibility, life cycle

Procedia PDF Downloads 122

Authors: Jugoslav Jokovic, Tijana Dimitrijevic, Nebojsa Doncov

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The goal of this paper is to investigate the possibilities and effectiveness of the TLM (Transmission Line Matrix) method for modelling of up-to-date microstrip antennas with circular geometry that have significant application in modern wireless communication systems. The coaxially fed microstrip antenna configurations with circular patch are analyzed by using the in-house 3DTLMcyl_cw solver based on computational electromagnetic TLM method adapted to the cylindrical grid and enhanced with the compact wire model. Opposed to the widely used rectangular TLM mesh, where a staircase approximation has to be used to describe curved boundaries, precise modelling of circular boundaries can be accomplished in the cylindrical grid irrespective of the mesh resolution. Using the compact wire model incorporated in cylindrical mesh, it is possible to model coaxial feed and include the influence of the real excitation in the antenna model. The conventional and inverted configuration of a coaxially fed circular patch antenna are considered, comparing the resonances obtained using TLM cylindrical model with results reached by the corresponding model in a rectangular grid as well as with experimental ones. Bearing in mind that accuracy of simulated results depends on a relevantly created model, besides structure geometry and dimensions, it is important to consider additional modelling issues, regarding appropriate mesh resolution and a relevant extension of a mesh around the considered structure that would provide convergence of the results.

Keywords: computational electromagnetic, coaxial feed, microstrip antenna, TLM modelling

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Authors: Jyoti Rani, Ashima Anand, Shivendra Shivani

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In recent years, physiological signals obtained in telemedicine have been stored independently from patient information. In addition, people have increasingly turned to mobile devices for information on health-related topics. Major authentication and security issues may arise from this storing, degrading the reliability of diagnostics. This study introduces an approach to reversible watermarking, which ensures security by utilizing the electrocardiogram (ECG) signal as a carrier for embedding patient information. In the proposed work, Pan-Tompkins++ is employed to convert the 1D ECG signal into a 2D signal. The frequency subbands of a signal are extracted using RDWT(Redundant discrete wavelet transform), and then one of the subbands is subjected to MSVD (Multiresolution singular valued decomposition for masking. Finally, the encrypted watermark is embedded within the signal. The experimental results show that the watermarked signal obtained is indistinguishable from the original signals, ensuring the preservation of all diagnostic information. In addition, the DnCNN (Denoising convolutional neural network) concept is used to denoise the retrieved watermark for improved accuracy. The proposed ECG signal-based watermarking method is supported by experimental results and evaluations of its effectiveness. The results of the robustness tests demonstrate that the watermark is susceptible to the most prevalent watermarking attacks.

Keywords: ECG, VMD, watermarking, PanTompkins++, RDWT, DnCNN, MSVD, chaotic encryption, attacks

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Authors: David Calderon Villegas, Thomas Kaltizky

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Run-of-river (RoR) hydropower projects represent a viable, clean, and cost-effective alternative to dam-based plants and provide decentralized power production. However, RoR schemes cost-effectiveness depends on the proper selection of site and design flow, which is a challenging task because it requires multivariate analysis. In this respect, this study presents the development of an investment decision support tool for assessing the optimal size of an RoR scheme considering the technical, environmental, and cost constraints. The net present value (NPV) from a project perspective is used as an objective function for supporting the investment decision. The tool has been tested by applying it to an actual RoR project recently proposed in Colombia. The obtained results show that the optimum point in financial terms does not match the flow that maximizes energy generation from exploiting the river's available flow. For the case study, the flow that maximizes energy corresponds to a value of 5.1 m3/s. In comparison, an amount of 2.1 m3/s maximizes the investors NPV. Finally, a sensitivity analysis is performed to determine the NPV as a function of the debt rate changes and the electricity prices and the CapEx. Even for the worst-case scenario, the optimal size represents a positive business case with an NPV of 2.2 USD million and an IRR 1.5 times higher than the discount rate.

Keywords: small hydropower, renewable energy, RoR schemes, optimal sizing, objective function

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Authors: M. G. Talasbayen, N. N. Dyussenbayev, Y. D. Kali, R. A. Zholbarysov, Y. N. Duissenbayev, I. Z. Mammadinova, S. M. Nuradilov

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Background. Hemorrhagic stroke is an acute cerebrovascular accident resulting from rupture of a cerebral vessel or increased permeability of the wall and imbibition of blood into the brain parenchyma. Arterial hypertension is a common cause of hemorrhagic stroke. Male gender and age over 55 years is a risk factor for intracerebral hemorrhage. Treatment of intracerebral hemorrhage is aimed at the primary pathophysiological link: the relief of coagulopathy and the control of arterial hypertension. Early surgical treatment can limit cerebral compression; prevent toxic effects of blood to the brain parenchyma. Despite progress in the development of neuroimaging data, the use of minimally invasive techniques, and navigation system, mortality from intracerebral hemorrhage remains high. Materials and methods. The study included 78 patients (62.82% male and 37.18% female) with a verified diagnosis of hemorrhagic stroke in the period from 2019 to 2021. The age of patients ranged from 25 to 80 years, the average age was 54.66±11.9 years. Demographic, brain CT data (localization, volume of hematomas), methods of treatment, and disease outcome were analyzed. Results. The retrospective analyze demonstrate that 78.2% of all patients underwent surgical treatment: decompressive craniectomy in 37.7%, craniotomy with hematoma evacuation in 29.5%, and hematoma draining in 24.59% cases. The study of the proportion of deaths, depending on the volume of intracerebral hemorrhage, shows that the number of deaths was higher in the group with a hematoma volume of more than 60 ml. Evaluation of the relationship between the time before surgery and mortality demonstrates that the most favorable outcome is observed during surgical treatment in the interval from 3 to 24 hours. Mortality depending on age did not reveal a significant difference between age groups. An analysis of the impact of the surgery type on mortality reveals that decompressive craniectomy with or without hematoma evacuation led to an unfavorable outcome in 73.9% of cases, while craniotomy with hematoma evacuation and drainage led to mortality only in 28.82% cases. Conclusion. Even though the multimodal approaches, the development of surgical techniques and equipment, and the selection of optimal conservative therapy, the question of determining the tactics of managing and treating hemorrhagic strokes is still controversial. Nevertheless, our experience shows that surgical intervention within 24 hours from the moment of admission and craniotomy with hematoma evacuation improves the prognosis of treatment outcomes.

Keywords: hemorragic stroke, Intracerebral hemorrhage, surgical treatment, stroke mortality

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Authors: Narendra Akhadkar, Philippe Delcambre

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In power protection and control products, assembly process variations due to the individual parts manufactured from single or multi-cavity tooling is a major problem. The dimensional and geometrical variations on the individual parts, in the form of manufacturing tolerances and assembly tolerances, are sources of clearance in the kinematic joints, polarization effect in the joints, and tolerance stack-up. All these variations adversely affect the quality of product, functionality, cost, and time-to-market. Variation simulation analysis may be used in the early product design stage to predict such uncertainties. Usually, variations exist in both manufacturing processes and materials. In the tolerance analysis, the effect of the dimensional and geometrical variations of the individual parts on the functional characteristics (conditions) of the final assembled products are studied. A functional characteristic of the product may be affected by a set of interrelated dimensions (functional parameters) that usually form a geometrical closure in a 3D chain. In power protection and control products, the prerequisite is: when a fault occurs in the electrical network, the product must respond quickly to react and break the circuit to clear the fault. Usually, the response time is in milliseconds. Any failure in clearing the fault may result in severe damage to the equipment or network, and human safety is at stake. In this article, we have investigated two important functional characteristics that are associated with the robust performance of the product. It is demonstrated that the experimental data obtained at the Schneider Electric Laboratory prove the very good prediction capabilities of the variation simulation performed using CETOL (tolerance analysis software) in an industrial context. Especially, this study allows design engineers to better understand the critical parts in the product that needs to be manufactured with good, capable tolerances. On the contrary, some parts are not critical for the functional characteristics (conditions) of the product and may lead to some reduction of the manufacturing cost, ensuring robust performance. The capable tolerancing is one of the most important aspects in product and manufacturing process design. In the case of miniature circuit breaker (MCB), the product's quality and its robustness are mainly impacted by two aspects: (1) allocation of design tolerances between the components of a mechanical assembly and (2) manufacturing tolerances in the intermediate machining steps of component fabrication.

Keywords: geometrical variation, product robustness, tolerance analysis, variation simulation

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Authors: Chiraz Ben Jabeur, Hassene Seddik

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In this paper, a full approach of modeling and control of a four-rotor unmanned air vehicle (UAV), known as quad-rotor aircraft, is presented. In fact, a PD and a PD optimized Neural Networks Approaches (PD-NN) are developed to be applied to control a quad-rotor. The goal of this work is to concept a smart self-tuning PD controller based on neural networks able to supervise the quad-rotor for an optimized behavior while tracking the desired trajectory. Many challenges could arise if the quad-rotor is navigating in hostile environments presenting irregular disturbances in the form of wind added to the model on each axis. Thus, the quad-rotor is subject to three-dimensional unknown static/varying wind disturbances. The quad-rotor has to quickly perform tasks while ensuring stability and accuracy and must behave rapidly with regard to decision-making facing disturbances. This technique offers some advantages over conventional control methods such as PD controller. Simulation results are obtained with the use of Matlab/Simulink environment and are founded on a comparative study between PD and PD-NN controllers based on wind disturbances. These later are applied with several degrees of strength to test the quad-rotor behavior. These simulation results are satisfactory and have demonstrated the effectiveness of the proposed PD-NN approach. In fact, this controller has relatively smaller errors than the PD controller and has a better capability to reject disturbances. In addition, it has proven to be highly robust and efficient, facing turbulences in the form of wind disturbances.

Keywords: hostile environment, PD and PD-NN controllers, quad-rotor control, robustness against disturbance

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Authors: Yeghnem Redha, Guerroudj Hicham Zakaria, Hanifi Hachemi Amar Lemiya, Meftah Sid Ahmed, Tounsi Abdelouahed, Adda Bedia El Abbas

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Creep deformation of concrete is often responsible for excessive deflection at service loads which can compromise the performance of elements within a structure. Although laboratory test may be undertaken to determine the deformation properties of concrete, these are time-consuming, often expensive and generally not a practical option. Therefore, relatively simple empirically design code models are relied to predict the creep strain. This paper reviews the accuracy of creep and shrinkage predictions of reinforced concrete (RC) shear walls structures strengthened with carbon fibre reinforced polymer (CFRP) sheets, which is characterized by a widthwise varying fibre volume fraction. This review is yielded by CEB-FIB MC90 model. The time-dependent behavior was investigated to analyze their static behavior. In the numerical formulation, the adherents and the adhesives are all modelled as shear wall elements, using the mixed finite element method. Several tests were used to dem¬onstrate the accuracy and effectiveness of the proposed method. Numerical results from the present analysis are presented to illustrate the significance of the time-dependency of the lateral displacements.

Keywords: RC shear walls strengthened, CFRP sheets, creep and shrinkage, CEB-FIP MC90 model, finite element method, static behavior

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Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

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Authors: Ndibarafinia Tobin

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Building defect and failure are common phenomena in the Nigerian construction industry. The activities of the inexperienced labor force in the Nigerian construction industry have tarnished the image of practicing construction professionals in recent past. Defects and collapse can cause unnecessary expenditure, delays, loss of lives, property and left many people injured. They are also generating controversies among parties involved. Also, if this situation is left unanswered and untreated, it will lead to more serious problems in the future upcoming construction projects in Nigeria. Quite a number of factors are responsible for collapse of high-rise, reinforced concrete buildings in Nigeria. Government, professional bodies and stakeholders are asking countless questions as to who should be responsible and how solutions could be proffered. Therefore this study is aimed to identify the contributing factors to high-rise buildings defects and failures in Nigeria, which frequently occur in construction project in order to minimize time and cost and also the roles of professionals and other participants play in the industry in terms of the use of building materials, placement and curing of concrete, modification in the use of a building, collapse of building induced by fire and other causes. The data is collected from questionnaire from various players in construction industry in Nigeria. This study is succeeds in identifying the causes of building failure and also suggesting possible measures to be taken by government and other regulatory bodies in the building industry to avert this and also improve the effectiveness of managing appraisal process of failures and defects in the future.

Keywords: building defects, building failures, Nigerian construction industry, professionals

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Authors: Auday Al-Mayyahi, Phil Birch, William Wang

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A vision system-based navigation for autonomous ground vehicle (AGV) equipped with a single camera in an indoor environment is presented. A proposed navigation algorithm has been utilized to detect obstacles represented by coloured mini- cones placed in different positions inside a corridor. For the recognition of the relative position and orientation of the AGV to the coloured mini cones, the features of the corridor structure are extracted using a single camera vision system. The relative position, the offset distance and steering angle of the AGV from the coloured mini-cones are derived from the simple corridor geometry to obtain a mapped environment in real world coordinates. The corridor is first captured as an image using the single camera. Hence, image processing functions are then performed to identify the existence of the cones within the environment. Using a bounding box surrounding each cone allows to identify the locations of cones in a pixel coordinate system. Thus, by matching the mapped and pixel coordinates using a projection transformation matrix, the real offset distances between the camera and obstacles are obtained. Real time experiments in an indoor environment are carried out with a wheeled AGV in order to demonstrate the validity and the effectiveness of the proposed algorithm.

Keywords: autonomous ground vehicle, navigation, obstacle avoidance, vision system, single camera, image processing, ultrasonic sensor

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Authors: Reza Karimpour

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Ports play a decisive role in the EU's external and internal trade, as about 74% of imports and exports and 37% of exchanges go through ports. Although ports, especially Deep Sea Shipping (DSS) ports, are integral nodes within multimodal logistic flows, Short Sea Shipping (SSS) and inland waterways are not so well integrated. The automated vessels and supply chain optimisations for sustainable shortsea shipping (MOSES) project aims to enhance the short sea shipping component of the European supply chain by addressing the vulnerabilities and strains related to the operation of large containerships. The MOSES concept can be shortly described as a large containership (mother-vessel) approaching a DSS port (or a large container terminal). Upon her arrival, a combined intelligent mega-system consisting of the MOSES Autonomous tugboat swarm for manoeuvring and the MOSES adapted AutoMoor system. Then, container handling processes are ready to start moving containers to their destination via hinterland connections (trucks and/or rail) or to be shipped to destinations near small ports (on the mainland or island). For the first case, containers are stored in a dedicated port area (Storage area), waiting to be moved via trucks and/or rail. For the second case, containers are stacked by existing port equipment near-dedicated berths of the DSS port. They then are loaded on the MOSES Innovative Feeder Vessel, equipped with the MOSES Robotic Container-Handling System that provides (semi-) autonomous (un) feeding of the feeder. The Robotic Container-Handling System is remotely monitored through a Shore Control Centre. When the MOSES innovative Feeder vessel approaches the small port, where her docking is achieved without tugboats, she automatically unloads the containers using the Robotic Container-Handling System on the quay or directly on trucks. As a result, ports with minimal or no available infrastructure may be effectively integrated with the container supply chain. Then, the MOSES innovative feeder vessel continues her voyage to the next small port, or she returns to the DSS port. MOSES exploitation activity mainly aims to exploit research outcomes beyond the project, facilitate utilisation of the pilot results by others, and continue the pilot service after the project ends. By the mid-lifetime of the project, the exploitation plan introduces the reader to the MOSES project and its key exploitable results. It provides a plan for delivering the MOSES innovations to the market as part of the overall exploitation plan.

Keywords: automated vessels, exploitation, shortsea shipping, supply chain

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Authors: Mary Ann Cristine R. Olgado

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Diversity in the classroom might make it difficult to promote individualized learning, but differentiated instruction that caters to students' various learning preferences may prove to be beneficial. Hence, this study examined the effectiveness of Hybrid-Differentiated Mathematics Instruction (HDMI) in improving the students’ academic performance in Mathematics. It employed the quasi-experimental research design by using a comparative analysis of the two variables: the experimental and control groups. The learning styles of the students were identified using the Grasha-Riechmann Student Learning Style Scale (GRSLSS), which served as the basis for designing differentiated action plans in Mathematics. In addition, adapted survey questionnaires, pre-tests, and post-tests were used to gather information and were analyzed using descriptive and correlational statistics to find the relationship between variables. The experimental group received differentiated instruction for a month, while the control group received traditional teaching instruction. The study found that Hybrid-Differentiated Mathematics Instruction (HDMI) improved the academic performance of Grade 11-TVL students, with the experimental group performing better than the control group. This program has effectively tailored the teaching methods to meet the diverse learning needs of the students, fostering and enhancing a deeper understanding of mathematical concepts in Statistics & Probability, both within and beyond the classroom.

Keywords: differentiated instruction, hybrid, learning styles, academic performance

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Authors: Atena Tazikeh Lemeski, Ismail Ozdamar

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This study presents a detailed analysis of harmonic distortion in a grid-connected photovoltaic (PV) system using real-time data captured from a solar power plant. Harmonics introduced by inverters in PV systems can degrade power quality and lead to increased Total Harmonic Distortion (THD), which poses challenges such as transformer overheating, increased power losses, and potential grid instability. This research addresses these issues by applying Fast Fourier Transform (FFT) to identify significant harmonic components and employing notch filters to target specific frequencies, particularly the 3rd harmonic (150 Hz), which was identified as the largest contributor to THD. Initial analysis of the unfiltered voltage signal revealed a THD of 21.15%, with prominent harmonic peaks at 150 Hz, 250 Hz and 350 Hz, corresponding to the 3rd, 5th, and 7th harmonics, respectively. After implementing the notch filters, the THD was reduced to 5.72%, demonstrating the effectiveness of this approach in mitigating harmonic distortion without affecting the fundamental frequency. This paper provides practical insights into the application of real-time filtering techniques in PV systems and their role in improving overall grid stability and power quality. The results indicate that targeted harmonic mitigation is crucial for the sustainable integration of renewable energy sources into modern electrical grids.

Keywords: grid-connected photovoltaic systems, fast Fourier transform, harmonic filtering, inverter-induced harmonics

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Authors: M. Farhaoui, M. Derraz

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Problem statement: In the water treatment processes, the coagulation and flocculation processes produce sludge according to the level of the water turbidity. The aluminum sulfate is the most common coagulant used in water treatment plants of Morocco as well as many countries. It is difficult to manage the sludge produced by the treatment plant. However, it can be used in the process to improve the quality of the treated water and reduce the aluminum sulfate dose. Approach: In this study, the effectiveness of sludge was evaluated at different turbidity levels (low, medium, and high turbidity) and coagulant dosage to find optimal operational conditions. The influence of settling time was also studied. A set of jar test experiments was conducted to find the sludge and aluminum sulfate dosages in order to improve the produced water quality for different turbidity levels. Results: Results demonstrated that using sludge produced by the treatment plant can improve the quality of the produced water and reduce the aluminum sulfate using. The aluminum sulfate dosage can be reduced from 40 to 50% according to the turbidity level (10, 20 and 40 NTU). Conclusions/Recommendations: Results show that sludge can be used in order to reduce the aluminum sulfate dosage and improve the quality of treated water. The highest turbidity removal efficiency is observed within 6 mg/l of aluminum sulfate and 35 mg/l of sludge in low turbidity, 20 mg/l of aluminum sulfate and 50 mg/l of sludge in medium turbidity and 20 mg/l of aluminum sulfate and 60 mg/l of sludge in high turbidity. The turbidity removal efficiency is 97.56%, 98.96% and 99.47% respectively for low, medium and high turbidity levels.

Keywords: coagulation process, coagulant dose, sludge, turbidity removal

Procedia PDF Downloads 331

Authors: Mukhammad Fatkhullah, Ayla Karina Budita, Cut Rizka Al Usrah, Kanita Khoirun Nisa, Muhammad Alhada Fuadilah Habib, Siti Muslihatul Mukaromah

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Batik industry has become one of the leading industries in the economy of Indonesia. Since the recognition of batik as one of cultural wealth and national identity of Indonesia by UNESCO, batik production keeps increasing as a result of increasing demands for batik, whether from domestically or abroad. One of the rapid development batik industries in Indonesia is batik industry in Lawean Village, Solo, Central Java, Indonesia. This batik industry generally uses putting-out system where batik workers work in their own houses. With the implementation of this system, therefore employers don’t have to prepare Environmental Impact Analysis (EIA), social security for workers, overtime payment, space for working, and equipment for working. The implementation of putting-out system causes many problems, starting from environmental pollution, the loss of social rights of workers, and even exploitation of workers by batik entrepreneurs. The data used to describe this reality is the primary data from qualitative research with in-depth interview data collection technique. Informants were determined purposively. The theory used to perform data interpretation is the phenomenology of Alfred Schutz. Both qualitative and phenomenology are used in this study to describe batik workers exploitation in terms of the implementation of putting-out system on home batik industry in Lawean. The research result showed that workers in batik industry sector in Lawean were exploited with the implementation of putting-out system. The workers were strictly employed by the entrepreneurs, so that their job cannot be called 'part-time' job anymore. In terms of labor and time, the workers often work more than 12 hours per day and they often work overtime without receiving any overtime payment. In terms of work safety, the workers often have contact with chemical substances contained in batik making materials without using any protection, such as clothes work, which is worsened by the lack of standard or procedure in work that can cause physical damage, such as burnt and peeled off skin. Moreover, exposure and contamination of chemical materials make the workers and their families vulnerable to various diseases. Meanwhile, batik entrepreneurs did not give any social security (including health cost aid). Besides that, the researchers found that batik industry in home industry sector is not environmentally friendly, even damaging ecosystem because industrial waste disposed without EIA.

Keywords: exploitation, home batik industry, occupational health and safety, putting-out system

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Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra

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Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I₁, I₂, … I_n at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.

Keywords: multi-temporal satellite image, urban growth, non-stationary, stochastic model

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Authors: Youmen Chaaban

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The study examined the influence of a situated professional development program (PD) aimed at enhancing English language teachers’ knowledge and skills and improving their instructional practices. The PD model under examination was developed upon sound theoretical underpinnings, taking into consideration research-based principles of effective PD. However, the implementation of the PD model within several school contexts required further investigation from the perspectives of the teachers, who were receiving the PD activities, and the instructional coaches, who were providing them. The paper, thus, presents the results of a qualitative study examining the perceptions of seventeen English language teachers and nineteen instructional coaches about the strengths of the PD program, the challenges they faced in the implementation of the program, and their suggestions for the improvement of the program’s implementation and outcomes. Comparisons were further made between the two groups of participants to uncover agreements and contradictions in their perceptions. Data were collected from the teachers through in-depth interviews and observations, while the data collected from the instructional coaches were open-ended surveys followed by focus group interviews. The findings of the study confirm the necessity of structuring PD activities around sound theoretical underpinnings. However, practical considerations specific to the contexts where the PD activities take place should be considered when evaluating the PD’s effectiveness. Finally, the study provides several recommendations for maximizing the influence of the PD program on teachers’ practices and beliefs.

Keywords: English language teachers, situated professional development, teacher beliefs, teacher practices

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Authors: Nasrin Badrkhani

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The increasing use of educational technologies has created a tremendous transformation in all fields and most importantly, in the field of education and learning. In recent decades, traditional learning approaches have undergone fundamental changes with the emergence of new learning technologies. Research shows that suitable educational tools play an effective role in the transmission, comprehension, and impact of educational concepts. These tools provide a tangible basis for thinking and constructing concepts, resulting in an increased interest in learning. They provide real and true experiences to students and convey educational meanings and concepts more quickly and clearly. It can be said that educational technology, as an active and modern teaching method, with capabilities such as engaging multiple senses in the educational process and involving the learner, makes the learning environment more flexible. It effectively impacts the skills of children with special needs by addressing their specific needs. Teachers are no longer the sole source of information, and students are not mere recipients of information. They are considered the main actors in the field of education and learning. Since education is one of the basic rights of every human being and children with special needs face unique challenges and obstacles in education, these challenges can negatively affect their abilities and learning. To combat these challenges, one of the ways is to use educational technologies for more diverse, effective learning. Also, the use of educational technology for students with special needs has increasingly proven effective in boosting their self-confidence and helping them overcome learning challenges, enhancing their learning outcomes.

Keywords: communication technology, students with special needs, self-confidence, raising the expectations and progress

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Authors: Jonathan Bolduc

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Studies have demonstrated the effectiveness of music training approaches to help children with language disabilities. Because music is closely associated with a number of cognitive functions, including language, it has been hypothesized that musical skills transfer to other domains. Research suggests that music training strengthens basic auditory processing skills in dyslexic children and may ameliorate phonological deficits. Furthermore, music instruction has the particular advantage of being non-literacy-based, thus removing the frustrations that can be associated with reading and writing activities among children with specific learning disabilities. In this study, we assessed the effect of implementing an intensive music program on the development of language skills (phonological and reading) in 4- to 9-year-old children. Seventeen children (N=17) participated in the study. The experiment took place over 6 weeks in a controlled environment. Eighteen lessons of 40 minutes were offered during this period by two music specialists. The Dalcroze, Orff, and Kodaly approaches were used. A series of qualitative measures were implemented to document the contribution of music training to this population. Currently, the data is being analyzed. The first results show that learning music seems to significantly improve verbal memory. We already know that language disabilities are considered one of the main causes of school dropout as well as later professional and social failure. We aim to corroborate that an integrated music education program can provide children with language disabilities with the same opportunities to develop and succeed in school as their classmates. Scientifically, the results will contribute to advance the knowledge by identifying the more effective music education strategies to improve the overall development of children worldwide.

Keywords: music education, music, art education, language diasabilities

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: automatic target recognition (ATR), high resolution range profile (HRRP), motion compensation, stepped frequency waveform technique (SFW), target motion parameters (TMPs)

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Authors: Jingchen Zhao

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Corporate social responsibility (CSR), a major contemporary focus for companies, governments, NGOs and communities, is discussed from a multi-disciplinary perspective. The term is introduced and defined to achieve a combination of economic, social, environmental and philanthropic goals, and its adoption in company law legislations in a few jurisdictions is discussed. Despite its positive social and environmental impacts, the notion has been widely criticised for being ill-defined and fundamentally flawed in the domain of corporate law. The value and effectiveness of CSR have been interrogated for many reasons, always inter-related. This article aims to consider and address some of these problems and assess how CSR could be sharpened and made more effective through the lens of accountability, focussing on the rationale behind and the means of regulation of CSR. The article aims to achieve two interrelated goals. First, it examines the function of accountability in the arguments in favour of CSR by investigating the extent to which the notion of accountability could be used as a criterion for regulating CSR, so that companies may be held accountable for corporate decisions affecting their stakeholders. Second, this article will examine the scope and goals of CSR and board accountability, creating the possibility of a more comprehensive understanding of the two notions from an interactive perspective. In order to link CSR and accountability closely to generate a more appropriate definition of CSR that is could be more appropriately and effectively applied in corporate law, the concept of corporate social accountability (CSA) will be evaluated, with the aim of broadening its latitude beyond disclosure. This will involve a rigorous assessment of the process of fulfilling directors’ duties via questioning from stakeholder groups during meetings or committees, together with explanations and justifications from the board. This will be followed by discussions on enforcement measures in relation to the concept of CSA.

Keywords: corporate governance, CSR, board accountability, corporate law

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Authors: Mojtaba Aghajari, Alireza Aghasi

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The first challenge which the current research faced has been the identification or determination of the level of knowledge in Isfahan public transportation corporation, and the second challenge has been the recognition and choice of a proper approach for the instructional system design. Responding these two challenges will present an appropriate model of instructional system design. In order to respond the first challenge or question, Nonaka and Takeuchi KM model has been utilized due to its universality among the 26 models proposed so far. The statistical population of this research included 2200 people, among which 200 persons were chosen as the sample of the research by the use of Morgan’s method. The data gathering has been carried out by the means of a questionnaire based on Nonaka and Takeuchi KM model, analysis of which has been done by SPSS program. The output of this questionnaire, yielding the point of 1.96 (out of 5 points), revealed that the general condition of Isfahan public transportation corporation is weak concerning its being knowledge-centered. After placing this output on Jonassen’s continuum, it was revealed that the appropriate approach for instructional system design is the system (or behavioral) approach. Accordingly, different steps of the general model of ADDIE, which covers all of the ISO10015 standards, were adopted in the act of designing. Such process in Isfahan public transportation corporation was designed and divided into three main steps, including: instructional designing and planning, instructional course planning, determination of the evaluation and the effectiveness of the instructional courses.

Keywords: instructional system design, system approach, knowledge management, employees

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Lori Lioce, Gary Maddux, Norven Goddard, Ishella Fogle, Bernard Schroer

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This paper presents the integration of technologies into nursing education. The collaborative effort includes the College of Nursing (CoN) at the University of Alabama in Huntsville (UAH) and the UAH Systems Management and Production Center (SMAP). The faculty at the CoN conducts needs assessments to identify education and training requirements. A team of CoN faculty and SMAP engineers then prioritize these requirements and establish improvement/development teams. The development teams consist of nurses to evaluate the models and to provide feedback and of undergraduate engineering students and their senior staff mentors from SMAP. The SMAP engineering staff develops and creates the physical models using 3D printing, silicone molds and specialized molding mixtures and techniques. The collaboration has focused on developing teaching and training, or clinical, simulators. In addition, the onset of the Covid-19 pandemic has intensified this relationship, as 3D modeling shifted to supplied personal protection equipment (PPE) to local health care providers. A secondary collaboration has been introducing students to clinical benchmarking through the UAH Center for Management and Economic Research. As a result of these successful collaborations the Model Exchange & Development of Nursing & Engineering Technology (MEDNET) has been established. MEDNET seeks to extend and expand the linkage between engineering and nursing to K-12 schools, technical schools and medical facilities in the region to the resources available from the CoN and SMAP. As an example, stereolithography (STL) files of the 3D printed models, along with the specifications to fabricate models, are available on the MEDNET website. Ten 3D printed models have been developed and are currently in use by the CoN. The following additional training simulators are currently under development:1) suture pads, 2) gelatin wound models and 3) printed wound tattoos. Specification sheets have been written for these simulations that describe the use, fabrication procedures and parts list. These specifications are available for viewing and download on MEDNET. Included in this paper are 1) descriptions of CoN, SMAP and MEDNET, 2) collaborative process used in product improvement/development, 3) 3D printed models of training and teaching simulators, 4) training simulators under development with specification sheets, 5) family care practice benchmarking, 6) integrating the simulators into the nursing curriculum, 7) utilizing MEDNET as a pandemic response, and 8) conclusions and lessons learned.

Keywords: 3D printing, nursing education, simulation, trainers

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Authors: Y. Mateyshina, A.Ulihin, N.Uvarov

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Electrolytes with different type of charge carrier can find widely application in different using, e.g. sensors, electrochemical equipments, batteries and others. One of important components ensuring stable functioning of the equipment is electrolyte. Electrolyte has to be characterized by high conductivity, thermal stability, and wide electrochemical window. In addition to many advantageous characteristic for liquid electrolytes, the solid state electrolytes have good mechanical stability, wide working range of temperature range. Thus search of new system of solid electrolytes with high conductivity is an actual task of solid state chemistry. Families of alkali perchlorates and nitrates have been investigated by us earlier. In literature data about transport properties of alkali nitrites are absent. Nevertheless, alkali nitrites MeNO2 (Me= Li+, Na+, K+, Rb+ and Cs+), except for the lithium salt, have high-temperature phases with crystal structure of the NaCl-type. High-temperature phases of nitrites are orientationally disordered, i.e. non-spherical anions are reoriented over several equivalents directions in the crystal lattice. Pure lithium nitrite LiNO2 is characterized by ionic conductivity near 10-4 S/cm at 180°C and more stable as compared with lithium nitrate and can be used as a component for synthesis of composite electrolytes. In this work composite solid electrolytes in the binary system LiNO2 - A (A= MgO, -Al2O3, Fe2O3, CeO2, SnO2, SiO2) were synthesized and their structural, thermodynamic and electrical properties investigated. Alkali nitrite was obtained by exchange reaction from water solutions of barium nitrite and alkali sulfate. The synthesized salt was characterized by X-ray powder diffraction technique using D8 Advance X-Ray Diffractometer with Cu K radiation. Using thermal analysis, the temperatures of dehydration and thermal decomposition of salt were determined.. The conductivity was measured using a two electrode scheme in a forevacuum (6.7 Pa) with an HP 4284A (Precision LCR meter) in a frequency range 20 Hz < ν < 1 MHz. Solid composite electrolytes LiNO2 - A A (A= MgO, -Al2O3, Fe2O3, CeO2, SnO2, SiO2) have been synthesized by mixing of preliminary dehydrated components followed by sintering at 250°C. In the series of nitrite of alkaline metals Li+-Cs+, the conductivity varies not monotonically with increasing radius of cation. The minimum conductivity is observed for KNO2; however, with further increase in the radius of cation in the series, the conductivity tends to increase. The work was supported by the Russian Foundation for Basic research, grant #14-03-31442.

Keywords: conductivity, alkali nitrites, composite electrolytes, transport properties

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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Authors: A. Iaaly, O. Jadayel, R. Jadayel

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This paper explores the effectiveness of approaches used for the implementation of technology within central governments specifically Geographic Information Systems (GIS). It examines the extent to which various strategies to GIS implementation and its roll out to users within an organization is crucial for its long term assimilation. Depending on the contextual requirements, various implementation strategies exist spanning from the most revolutionary to the most evolutionary, which have an influence on the success of GIS projects and the realization of resulting business benefits within the central governments. This research compares between two strategies of GIS implementation within the Lebanese Municipalities. The first strategy is the “Technological Approach” which is focused on technology acquisition, overlaid on existing governmental frameworks. This approach gives minimal attention to capability building and the long term sustainability of the implemented program. The second strategy, referred to as the “Ecological Approach”, is naturally oriented to the function of the organization. This approach stresses on fostering the evolution of the program and on building the human capabilities. The Union of the Joumeh Municipalities will be presented as a case study under the “Ecological Approach” and the role of the GIS Center at the University of Balamand will be highlighted. Thus, this research contributes to the development of knowledge on technology implementation and the vital role of academia in the specific context of the Lebanese public sector so that this experience may pave the way for further applications.

Keywords: ecological approach GIS, low income countries, technological approach

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Authors: Vinay Kumar Theendra

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The main objective of the study is to evaluate the effectiveness of hesperidin in the treatment of breast cancer and causing less (or) no bone marrow depression which is the major side effect of the present anticancer drugs treating breast cancer, also to evaluate the mechanisms through which these compounds are exerting their effect. Breast cancer is induced by administering N-methyl N-Nitrosourea (MNU) at a dose of 50mg/kg body weight. Upon the termination of the experiment, the animals were sacrificed by the method of cervical dislocation. The animals were dissected along the ventral midline and were grossly examined for the presence of tumors. Then the tumours were removed along with the stroma. Vascular endothelial growth factor (VEGF) levels were estimated by using ELISA method. The first occurrence of palpable tumors was eight weeks after carcinogen treatment and the final tumour incidence was 100% in the MNU alone and topical treated rats. Whereas in rats of other treatment groups there is decreased tumour incidence which might be due to their antitumour activity. Hesperidin therapy inhibited angiogenesis which can be evident from the significant reduction in serum as well as tumour VEGF concentrations in comparison to the untreated mammary carcinoma bearing rats. Hesperidin is promising agents that exert direct antitumor and also antiangiogenic, antiproliferative and anti-inflammatory activities. Even though the potency is little lesser than standard drug vincristine, it has been proved to be safe without effecting haematological count.

Keywords: hesperidin, VEGF, COX 2, N-methyl N-nitrosourea

Procedia PDF Downloads 135