Search results for: Coefficient of Performance

Authors: P. Ghosh, S. B. Sharma

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The growing problem of food waste is causing unacceptable economic, environmental and social impacts across the globe. In Australia, food waste is estimated at about AU$8 billion per year; however, information on the extent of wastage at different stages of the food value chain from farm to fork is very limited. This study aims to identify causes for and extent of food waste at wholesaler stage of the food value chain in the state of Western Australia. It also explores approaches applied to reduce and utilize food waste by the wholesalers. The study was carried out at Perth city market in Caning Vale, the main wholesale distribution centre for fruits and vegetables in Western Australia. A survey questionnaire was prepared and shared with 51 wholesalers and their responses to 10 targeted questions on quantity of produce (fruits and vegetables) delivery received and further supplied, reasons for waste generation and innovations applied or being considered to reduce and utilize food waste. Data were computed using the Statistical Package for the Social Sciences (SPSS version 21). Among the wholesalers 52% were primary wholesalers (buy produce directly from growers) and 48% were secondary wholesalers (buy produce in bulk from major wholesalers and supply to the local retail market, caterers, and customers with specific requirements). Average fruit and vegetable waste was 180 Kilogram per week per primary wholesaler and 30 Kilogram per secondary wholesaler. Based on this survey, the fruit and vegetable waste at wholesaler stage was estimated at about 286 tonnes per year. The secondary wholesalers distributed pre-ordered commodities, which minimized the potential to cause waste. Non-parametric test (Mann Whitney test) was carried out to assess contributions of wholesalers to waste generation. Over 56% of secondary wholesalers generally had nothing to bin as waste. Pearson’s correlation coefficient analysis showed positive correlation (r = 0.425; P=0.01) between the quantity of produce received and waste generated. Low market demand was the predominant reason identified by the wholesalers for waste generation. About a third of the wholesalers suggested that high cosmetic standards for fruits and vegetables - appearance, shape, and size - should be relaxed to reduce waste. Donation of unutilized fruits and vegetables to charity was overwhelmingly (95%) considered as one of the best options for utilization of discarded produce. The extent of waste at other stages of fruit and vegetable supply chain is currently being studied.

Keywords: food waste, fruits and vegetables, supply chain, waste generation

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Authors: A. Assad, T. Zayed

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Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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Authors: Sree Bash Chandra Debnath, Didier Tonneau, Carole Fauquet, Agnes Tallet, Julien Darreon

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Purpose: Inorganic scintillating dosimetry is the most recent promising technique to solve several dosimetric issues and provide quality assurance in radiation therapy. Despite several advantages, the major issue of using scintillating detectors is the Cerenkov effect, typically induced in the visible emission range. In this context, the purpose of this research work is to evaluate the performance of a novel infrared inorganic scintillator detector (IR-ISD) in the radiation therapy treatment to ensure Cerenkov free signal and the best matches between the delivered and prescribed doses during treatment. Methods: A simple and small-scale infrared inorganic scintillating detector of 100 µm diameter with a sensitive scintillating volume of 2x10-6 mm3 was developed. A prototype of the dose verification system has been introduced based on PTIR1470/F (provided by Phosphor Technology®) material used in the proposed novel IR-ISD. The detector was tested on an Elekta LINAC system tuned at 6 MV/15MV and a brachytherapy source (Ir-192) used in the patient treatment protocol. The associated dose rate was measured in count rate (photons/s) using a highly sensitive photon counter (sensitivity ~20ph/s). Overall measurements were performed in IBATM water tank phantoms by following international Technical Reports series recommendations (TRS 381) for radiotherapy and TG43U1 recommendations for brachytherapy. The performance of the detector was tested through several dosimetric parameters such as PDD, beam profiling, Cerenkov measurement, dose linearity, dose rate linearity repeatability, and scintillator stability. Finally, a comparative study is also shown using a reference microdiamond dosimeter, Monte-Carlo (MC) simulation, and data from recent literature. Results: This study is highlighting the complete removal of the Cerenkov effect especially for small field radiation beam characterization. The detector provides an entire linear response with the dose in the 4cGy to 800 cGy range, independently of the field size selected from 5 x 5 cm² down to 0.5 x 0.5 cm². A perfect repeatability (0.2 % variation from average) with day-to-day reproducibility (0.3% variation) was observed. Measurements demonstrated that ISD has superlinear behavior with dose rate (R2=1) varying from 50 cGy/s to 1000 cGy/s. PDD profiles obtained in water present identical behavior with a build-up maximum depth dose at 15 mm for different small fields irradiation. A low dimension of 0.5 x 0.5 cm² field profiles have been characterized, and the field cross profile presents a Gaussian-like shape. The standard deviation (1σ) of the scintillating signal remains within 0.02% while having a very low convolution effect, thanks to lower sensitive volume. Finally, during brachytherapy, a comparison with MC simulations shows that considering energy dependency, measurement agrees within 0.8% till 0.2 cm source to detector distance. Conclusion: The proposed scintillating detector in this study shows no- Cerenkov radiation and efficient performance for several radiation therapy measurement parameters. Therefore, it is anticipated that the IR-ISD system can be promoted to validate with direct clinical investigations, such as appropriate dose verification and quality control in the Treatment Planning System (TPS).

Keywords: IR-Scintillating detector, dose measurement, micro-scintillators, Cerenkov effect

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Authors: Gubhinder Kundhi, Paul Rilstone

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It is well established that Instrumental Variable (IV) estimators in the presence of weak instruments can be poorly behaved, in particular, be quite biased in finite samples. Finite sample approximations to the distributions of these estimators are obtained using Edgeworth and Saddlepoint expansions. Departures from normality of the distributions of these estimators are analyzed using higher order analytical corrections in these expansions. In a Monte-Carlo experiment, the performance of these expansions is compared to the first order approximation and other methods commonly used in finite samples such as the bootstrap.

Keywords: bootstrap, Instrumental Variable, Edgeworth expansions, Saddlepoint expansions

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Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

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Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

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Authors: Ali Nabavi, Farimah Safari, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Hossein Molavi Vardanjani

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Cognitive impairment presents a significant and increasing health concern as populations age. Environmental risk factors such as heavy metal exposure are suspected contributors, but their specific roles remain incompletely understood. Machine learning offers a promising approach to integrate multi-factorial data and improve the prediction of cognitive outcomes. This study aimed to develop and validate machine learning models to predict early risk of cognitive impairment by incorporating demographic, clinical, and biomarker data, including measures of heavy metal exposure. A retrospective analysis was conducted using 2011-2014 National Health and Nutrition Examination Survey (NHANES) data. The dataset included participants aged 20 years and older who underwent cognitive testing. Variables encompassed demographic information, medical history, lifestyle factors, and biomarkers such as blood and urine levels of lead, cadmium, manganese, and other metals. Machine learning algorithms were trained on 90% of the data and evaluated on the remaining 10%, with performance assessed through metrics such as accuracy, area under curve (AUC), and sensitivity. Analysis included 2,933 participants. The stacking ensemble model demonstrated the highest predictive performance, achieving an AUC of 0.778 and a sensitivity of 0.879 on the test dataset. Key predictors included age, gender, hypertension, education level, urinary cadmium, and blood manganese levels. The findings indicate that machine learning can effectively predict the risk of cognitive impairment using a comprehensive set of clinical and environmental exposure data. Incorporating biomarkers of heavy metal exposure improved prediction accuracy and highlighted the role of environmental factors in cognitive decline. Further prospective studies are recommended to validate the models and assess their utility over time.

Keywords: cognitive impairment, heavy metal exposure, predictive models, aging

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Authors: Babajide S. Adeokin, Oguntoyinbo O. Kazeem

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The not so pleasing state of the nation's quality of education has been a major area of research. Many researchers have looked into various aspects of the educational system and organizational structure in relation to the quality of service delivery of the staff members. However, there is paucity of research in areas relating to the sense of competence and commitment in relation to leadership styles. Against this backdrop, this study investigated the impact of leadership style and sense of competence on the performance of post-primary school teachers in Oyo state Nigeria. Data were generated across public secondary schools in the city using survey design method. Ibadan as a metropolis has eleven local government areas contained in it. A systematic random sampling technique of the eleven local government areas in Ibadan was done and five local government areas were selected. The selected local government areas are Akinyele, Ibadan North, Ibadan North-East, Ibadan South and Ibadan South-West. Data were obtained from a range of two – three public secondary schools selected in each of the local government areas mentioned above. Also, these secondary schools are a representation of the variations in the constructs under consideration across the Ibadan metropolis. Categorically, all secondary school teachers in Ibadan were clustered into selected schools in those found across the five local government areas. In all, a total of 272 questionnaires were administered to public secondary school teachers, while 241 were returned. Findings revealed that transformational leadership style makes room for job commitment when compared with transactional and laissez-faire leadership styles. Teachers with a high sense of competence are more likely to demonstrate more commitment to their job than others with low sense of competence. We recommend that, it is important an assessment is made of the leadership styles employed by principals and school administrators. This guides administrators and principals in to having a clear, comprehensive knowledge of the style they currently adopt in the management of the staff and the school as a whole; and know where to begin the adjustment process from. Also to make an impact on student achievement, being attentive to teachers’ levels of commitment may be an important aspect of leadership for school principals.

Keywords: Ibadan, leadership style, sense of competence, teachers, public secondary schools

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Authors: Geun-Yeon Kim, S. P. Praveen Kumar, Kwon-Hee Lee

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A steering knuckle arm is the component that connects the steering system and suspension system. The structural performances such as stiffness, strength, and durability are considered in its design process. The former study suggested the lightweight design of a knuckle arm considering the structural performances and using the metamodel-based optimization. The six shape design variables were defined, and the optimum design was calculated by applying the kriging interpolation method. The finite element method was utilized to predict the structural responses. The suggested knuckle was made of the aluminum Al6082, and its weight was reduced about 60% in comparison with the base steel knuckle, satisfying the design requirements. Then, we investigated its manufacturability by performing foraging analysis. The forging was done as hot process, and the product was made through two-step forging. As a final step of its developing process, the durability is investigated by using the flexible dynamic analysis software, LS-DYNA and the pre and post processor, eta/VPG. Generally, a car make does not provide all the information with the part manufacturer. Thus, the part manufacturer has a limit in predicting the durability performance with the unit of full car. The eta/VPG has the libraries of suspension, tire, and road, which are commonly used parts. That makes a full car modeling. First, the full car is modeled by referencing the following information; Overall Length: 3,595mm, Overall Width: 1,595mm, CVW (Curve Vehicle Weight): 910kg, Front Suspension: MacPherson Strut, Rear Suspension: Torsion Beam Axle, Tire: 235/65R17. Second, the road is selected as the cobblestone. The road condition of the cobblestone is almost 10 times more severe than that of usual paved road. Third, the dynamic finite element analysis using the LS-DYNA is performed to predict the durability performance of the suggested knuckle arm. The life of the suggested knuckle arm is calculated as 350,000km, which satisfies the design requirement set up by the part manufacturer. In this study, the overall design process of a knuckle arm is suggested, and it can be seen that the developed knuckle arm satisfies the design requirement of the durability with the unit of full car. The VPG analysis is successfully performed even though it does not an exact prediction since the full car model is very rough one. Thus, this approach can be used effectively when the detail to full car is not given.

Keywords: knuckle arm, structural optimization, Metamodel, forging, durability, VPG (Virtual Proving Ground)

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Authors: Lorenza Fabiocchi, Marco Mariani, Andrea Lucchini Huspek, Matteo Pozzi, Massimiliano Bestetti, Serena Graziosi, Nora Lecis

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Additive manufacturing of stainless steels is rapidly developing thanks to the ability to achieve complex designs effortlessly. Stainless steel 17-4PH is valued for its high strength and corrosion resistance, however intricate geometries are challenging to obtain due to rapid tool wear when machined. Binder jetting additive manufacturing was used to produce 17–4PH samples and pulsed electron beam surface treatment was investigated to enhance surface properties of components. The aim is to improve the tribological performance compared to the as-sintered condition and the H900 aging process, which optimizes hardness and wear resistance. Printed samples were sintered in a reducing atmosphere and superficially treated with an electron beam by varying the voltage (20 - 25 - 30 kV) and pulse count (20 – 40 pulses). Then, the surface was characterized from a microstructural and mechanical standpoint. Scratch tests were performed, and a reciprocating linear pin-on-disk wear test was conducted at 2 N and 10 Hz. Results showed that the voltage affects the roughness and thickness of the treated layer, whilst the number of pulses influences the hardening of the microstructure and consequently the wear resistance. Treated samples exhibited lower coefficients of friction compared to as-printed surfaces, though the values approached those of aged samples after the abrasion of the melted layer, indicating a deeper heat-affected zone formation. Different amounts of residual stress in the heat effected zone were individuated through the scratch tests. Still, the friction remained lower than that of as-printed specimens. This study demonstrates that optimizing electron beam parameters is vital for achieving surface performance comparable to bulk aging treatments, with significant implications for long-term wear resistance.

Keywords: low energy high current pulsed electron beam, tribology, binder jetting 3D printing, 17-4PH stainless steel

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Authors: Gyo Woo Lee, Man Young Kim

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The blocked-off formulations for the analysis of radiative heat transfer are formulated and examined in order to find the solutions in a two-dimensional complex enclosure. The final discretization equations using the step scheme for spatial differencing practice are proposed with the additional source term to incorporate the blocked-off procedure. After introducing the implementation for inactive region into the general discretization equation, three different problems are examined to find the performance of the solution methods.

Keywords: radiative heat transfer, Finite Volume Method (FVM), blocked-off solution procedure, body-fitted coordinate

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Authors: Mingqian Zhang

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Tip-enhanced Raman spectroscopy (TERS) is a scanning probe technique for individual objects and structured surfaces investigation that provides a wealth of enhanced spectral information with nanoscale spatial resolution and high detection sensitivity. It has become a powerful and promising chemical and physical information detection method in the nanometer scale. The TERS technique uses a sharp metallic tip regulated in the near-field of a sample surface, which is illuminated with a certain incident beam meeting the excitation conditions of the wave-vector matching. The local electric field, and, consequently, the Raman scattering, from the sample in the vicinity of the tip apex are both greatly tip-enhanced owning to the excitation of localized surface plasmons and the lightning-rod effect. Typically, a TERS setup is composed of a scanning probe microscope, excitation and collection optical configurations, and a Raman spectroscope. In the illumination configuration, an objective lens or a parabolic mirror is always used as the most important component, in order to focus the incident beam on the tip apex for excitation. In this research, a novel TERS setup was built up by introducing a plasmonic lens to the excitation optics as a focusing device. A plasmonic lens with symmetry breaking semi-annular slits corrugated on gold film was designed for the purpose of generating concentrated sub-wavelength light spots with strong longitudinal electric field. Compared to conventional far-field optical components, the designed plasmonic lens not only focuses an incident beam to a sub-wavelength light spot, but also realizes a strong z-component that dominants the electric field illumination, which is ideal for the excitation of tip-enhancement. Therefore, using a PL in the illumination configuration of TERS contributes to improve the detection sensitivity by both reducing the far-field background and effectively exciting the localized electric field enhancement. The FDTD method was employed to investigate the optical near-field distribution resulting from the light-nanostructure interaction. And the optical field distribution was characterized using an scattering-type scanning near-field optical microscope to demonstrate the focusing performance of the lens. The experimental result is in agreement with the theoretically calculated one. It verifies the focusing performance of the plasmonic lens. The optical field distribution shows a bright elliptic spot in the lens center and several arc-like side-lobes on both sides. After the focusing performance was experimentally verified, the designed plasmonic lens was used as a focusing component in the excitation configuration of TERS setup to concentrate incident energy and generate a longitudinal optical field. A collimated linearly polarized laser beam, with along x-axis polarization, was incident from the bottom glass side on the plasmonic lens. The incident light focused by the plasmonic lens interacted with the silver-coated tip apex and enhanced the Raman signal of the sample locally. The scattered Raman signal was gathered by a parabolic mirror and detected with a Raman spectroscopy. Then, the plasmonic lens based setup was employed to investigate carbon nanotubes and TERS experiment was performed. Experimental results indicate that the Raman signal is considerably enhanced which proves that the novel TERS configuration is feasible and promising.

Keywords: longitudinal electric field, plasmonics, raman spectroscopy, tip-enhancement

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Authors: Urom Scholastica Mgbo, Ifeanyichukwu, Vivian, Anaba, Uchemadu Martins, Arusiaba, Nelson Chijioke

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The study was investigated to determine the growth performance , haematological and serum biochemistry of broiler fed graded levels of cocoyam (Xanthosoma sagittifolium). One hundred and twenty (120) day old broiler chicks of Anak strain were used for the study. The birds were randomly divided into 4 treatment groups of 30 birds per group, and each group was further divided into 3 replicates of 10 birds per replicate in group. Cooked cocoyam was used to formulate diets at inclusion levels of 0.00% for T1 (control), while T2, T3 and T4 contained 10.00%, 20.00% and 30.00% inclusion of cocoyam in partial replacement of maize in a Completely Randomized Design (CRD). At the end of the research, the haematological indices of broiler showed that packed cell volume (PCV) of birds fed diets 1(42.26%) and 3 (42.42%) were significantly (p<0.05) higher than birds fed diets 2 (39.72%) and 4 (38.78%).The Haemoglobin (Hb) of birds fed diets 3 (12.58g/dl) and 4 (12.26g/dl) were significantly (p<0.05) higher than birds fed diets 1 (11.60g/dl) and 2 (11.42g/dl). The values of the white blood cell (WBC) of the broiler chickens placed on cocoyam diet increased significantly (P<0.05) compared with the values obtained in the control (T1) . The serum protein value for birds fed diet I (5.45g/dl) were statistically (P>0.05) similar to those fed diets 2 (5.10g/dl) and 3 (5.38g/dl) but differ significantly (P<0.05) from diet 4 (4.97g/dl) which had the least protein value. Final weight of the birds showed that diet 4 (2370.85g) had the highest (P<0.05) value which was followed closely by diet 3 (2225.55g), while birds fed diets 1 (2165.70g) and diet 2 (2145.00g) recorded the least values Similar pattern was observed in the weight gain of the birds. Birds fed diet 4 (2270.30g) had higher (P<0.05) value, followed by birds on diet 3 (2125.45g), while birds fed diet 1 (2065.15g) and 2 (2044.90g) had the least values.. This study showed that birds fed diet 3 (50.60g) and diet 4 (54.05g) gave significantly (P<0.05) higher weight than the control diet (49.17g). There was significant (P<0.05) difference among the treatments for feed conversion ratio (FCR), were birds fed diet 4 (1.74) performed better, having the least feed conversion ratio. Economics of broiler chickens showed that Cost/kg of feed favored diet 4 (₦158.65) followed by diets 3 (₦165.95), 2 (₦178.52) and control diet 1 (₦197.14). From the result, the higher weight recorded in T4 4 showed that cocoyam meal can successfully replace maize up to 30% in the diet of broiler chickens. The low cost recorded in cocoyam based diets showed that the diets were more economical and beneficial compared to control diet 1. Therefore, feeding diet 4 (30%) cocoyam meal as replacement of maize in broiler chickens is recommended.

Keywords: cocoyam, growth, heamatology, serum biochemistry

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Authors: Nathalie Elia, Samer Aouad, Jane Estephane, Christophe Poupin, Bilal Nsouli, Edmond Abi Aad

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Carbon dioxide is one of the main contributors to greenhouse effect and hence to climate change. As a result, the methanation reaction CO2(g) + 4H2(g) →CH4(g) + 2H2O (ΔH°298 = -165 kJ/mol), also known as Sabatier reaction, has received great interest as a process for the valorization of the greenhouse gas CO2 into methane which is a hydrogen-carrier gas. The methanation of CO2 is an exothermic reaction favored at low temperature and high pressure. However, this reaction requires a high energy input to activate the very stable CO2 molecule, and exhibits serious kinetic limitations. Consequently, the development of active and stable catalysts is essential to overcome these difficulties. Catalytic methanation of CO2 has been studied using catalysts containing Rh, Pd, Ru, Co and Ni on various supports. Among them, the Ni-based catalysts have been extensively investigated under various conditions for their comparable methanation activity with highly improved cost-efficiency. The addition of promoters are common strategies to increase the performance and stability of Ni catalysts. In this work, a small amount of Ru was used as a promoter for Ni catalysts supported on ceria and tested in the CO2 methanation reaction. The nickel loading was 5 wt. % and ruthenium loading is 0.5wt. %. The catalysts were prepared by successive impregnation method using Ni(NO3)2.6H2O and Ru(NO)(NO3)3 as precursors. The calcined support was impregnated with Ni(NO3)2.6H2O, dried, calcined at 600°C for 4h, and afterward, was impregnated with Ru(NO)(NO3)3. The resulting solid was dried and calcined at 600°C for 4 h. Supported monometallic catalysts were prepared likewise. The prepared solids Ru(0.5%)/CeO2, Ni(5%)/CeO2 and Ru(0.5%)-Ni(5%)/CeO2 were then reduced prior to the catalytic test under a flow of 50% H2/Ar (50 ml/min) for 4h at 500°C. Finally, their catalytic performances were evaluated in the CO2 methanation reaction, in the temperature range of 100–350°C by using a gaseous mixture of CO2 (10%) and H2 (40%) in Ar balanced at a total flow rate of 100 mL/min. The effect of pressure on the CO2 methanation was studied by varying the pressure between 1 and 10 bar. The various catalysts showed negligible CO2 conversion at temperatures lower than 250°C. The conversion of CO2 increases with increasing reaction temperature. The addition of Ru as promoter to Ni/CeO2 improved the CO2 methanation. It was shown that the CO2 conversion increases from 15 to 70% at 350°C and 1 bar. The effect of pressure on CO2 conversion was also studied. Increasing the pressure from 1 to 5 bar increases the CO2 conversion from 70% to 87%, while increasing the pressure from 5 to 10 bar increases the CO2 conversion from 87% to 91%. Ru–Ni catalysts showed excellent catalytic performance in the methanation of carbon dioxide with respect to Ni catalysts. Therefore the addition of Ru onto Ni catalysts improved remarkably the catalytic activity of Ni catalysts. It was also found that the pressure plays an important role in improving the CO2 methanation.

Keywords: CO2, methanation, nickel, ruthenium

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Authors: Hsiao Hsun Yuan

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Internal marketing was proposed in 1970s. The theory of the concept has continually changed over the past forty years. This study discussed the following themes: the definition and implication of internal marketing, the progress of its development, and the evolution of its theoretical model. Moreover, the study systematically organized the strategies of the internal marketing theory adopted on enterprise and how they were put into practice. It also compared the empirical studies focusing on how the existent theories influenced the important variables of internal marketing. The results of this study are expected to serve as references for future exploration of the boundary and studies aiming at how internal marketing is applied to different types of enterprises.

Keywords: corporate responsibility, employee organizational performance, internal marketing, internal customer

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Authors: M. A. Yazdi, J. Yang, L. Yihui, H. Su

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The application of recycle waste tires into civil engineering practices, namely asphalt paving mixtures and cementbased materials has been gaining ground across the world. This review summarizes and compares the recent achievements in the area of plain rubberized concrete (PRC), in details. Different treatment methods have been discussed to improve the performance of rubberized Portland cement concrete. The review also includes the effects of size and amount of tire rubbers on mechanical and durability properties of PRC. The microstructure behaviour of the rubberized concrete was detailed.

Keywords: waste rubber aggregates, microstructure, treatment methods, size and content effects

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Authors: Mohadeseh Seyednezhad, Armin Rajabi, Andanastui Muchtar, Mahendra Rao Somalu

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This work investigates the electrical properties of NiO-SDC/SDC anode sintered at about 1200 ○C for 1h through a relatively new approach, namely the microwave method. Nano powders Sm0.2Ce0.8O1.9 (SDC) and NiO were mixed by using a high-energy ball-mill and subsequent co-pressed at three different compaction pressures 200, 300 and 400 MPa. The novelty of this study consists in the effect of compaction pressure on the electrochemical performance of Ni-SDC/SDC anode, with no binder used between layers. The electrical behavior of the prepared anode has been studied by electrochemical impedance spectra (EIS) in controlled atmospheres, operating at high temperatures (600-800 °C).

Keywords: sintering, fuel cell, electrical conductivity, nanostructures, impedance spectroscopy, ceramics

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Authors: Jeffrey Siphiwe Mkhize

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Twelve years of schooling for most South African children, particularly those children from disadvantaged past, are confronted with numerous and diverse challenges. These challenges range from infrastructural limitations, language of teaching, poor resources and varying family backgrounds. Likewise, schools are categorized to signify schools’ geographic location, poverty lines, societal class and type of students that the school are likely to enroll. Such categorization perpetuates particular lines of identities that are indirectly reinforced by the same system that seeks to redress. South African universities prefer point systems to determine students’ suitability to gain access to their programmes. Once students are admitted based on the qualifying points there is an assumed equity in the manner in which they receive tuition. They are assumed as equal; noting the widened access to South African universities as means to redress past inequalities. Given the challenges, inequalities, it is necessary to view higher education as a site for knowledge construction that is accessible to all students. Epistemological access is key to all students irrespective of their socio-economic status. This paper seeks to contribute to the discourse of student engagement using lecturer-student relationship as a lens to understand this phenomenon. Data were generated using South African Survey of Student Engagement, focus group interviews, semi-structured one-on-one-interviews as well as document analysis. The focus was on students registered for the first year of a Bachelor of Education degree as well as lecturers that teach high risk modules in this qualification at the same level. The findings suggest that lecturers are challenged by overcrowded classrooms and over-enrolled modules; this challenge hampers their good intentions to become more efficient and innovative in their teaching. Students lack confidence in approaching lecturers for assistance. Collaborative learning has stronger results and students believe in self-support to deal with their challenges based on their individual strengths. Collaborative learning is key to student academic performance.

Keywords: collaborative learning, consultations, student engagement, student performance

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Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

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The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: Mohammed A. Hajeeh

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This paper examines the behavior of a system, which upon failure is either replaced with certain probability p or imperfectly repaired with probability q. The system is analyzed using Kolmogorov's forward equations method; the analytical expression for the steady state availability is derived as an indicator of the system’s performance. It is found that the analysis becomes more complex as the number of imperfect repairs increases. It is also observed that the availability increases as the number of states and replacement probability increases. Using such an approach in more complex configurations and in dynamic systems is cumbersome; therefore, it is advisable to resort to simulation or heuristics. In this paper, an example is provided for demonstration.

Keywords: repairable models, imperfect, availability, exponential distribution

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Authors: Nora Arbaoui, Rachid Tadili

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The substantial increase of areas cultivated under glasshouses compels the use of other natural heating and cooling procedures to make a profit as well as avoid both exorbitant fuel consumption and CO₂ emissions. This experimental study is designed to examine the functioning of a solar heating system that will increase positive consequences in terms of both quantity and quality while successfully enhancing greenhouse microclimate during wintertime. Those configurations have been tested in a miniaturized greenhouse simply after having optimized the operating parameters. These were noteworthy results when compared to an unheated witness greenhouse.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

Procedia PDF Downloads 150

Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Peng Liu

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Deep Q networks (DQNs) represent a significant advancement in reinforcement learning, utilizing neural networks to approximate the optimal Q-value for guiding sequential decision processes. This paper presents a comprehensive introduction to reinforcement learning principles, delves into the mechanics of DQNs, and explores its application in portfolio optimization. By evaluating the performance of DQNs against traditional benchmark portfolios, we demonstrate its potential to enhance investment strategies. Our results underscore the advantages of DQNs in dynamically adjusting asset allocations, offering a robust portfolio management framework.

Keywords: deep reinforcement learning, deep Q networks, portfolio optimization, multi-period optimization

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Authors: Yolanda Ramirez, Angel Tejada, Agustin Baidez

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In the knowledge-based economy, intangible elements are considered essential in order to achieve competitive advantage in organizations. In this sense, the Balanced Scorecard is a very suitable tool to recognize value and manage intangibles because it translates an organization’s strategic objectives into a set of performance indicators from a financial, as well as customer perspective, internal process and learning and growth perspectives. The aim of this paper is to expose and justify the benefits that the Balanced Scorecard might have for identifying, measuring and managing intellectual capital at universities, by means of reviewing the most important Balanced Scorecard implementations at Spanish public universities.

Keywords: knowledge management, balanced scorecard, universities, Spain

Procedia PDF Downloads 282

Authors: M. Zyczkowski, P. Markowski, M. Karol

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The security industry is making many efforts to lower the costs of system installation. However, the dominant technique is the application of fiber optic sensors. It is necessary to determine the location of the disorder of long optical fiber cables. For a number of years, many research centers developed their own solutions. The article presents the construction of the sensor systems with the possibility of disorder location. We present a methodology for determining location of the disorder. The aim of investigations is to answer the question of which of optical sensor configuration offer the best performance for location of the disorder.

Keywords: fiber optic sensor, security sensor, fiber cables, system instillation

Procedia PDF Downloads 640

Authors: Bakari Mohammed

Abstract:

Sports performance and achievements have been the avenue through which great nations of the world exhibit their supremacy over others through sports development strategy. Effective sports development, therefore, requires variables like sports policy, sports funding, sports programme, sports facilities and sponsorship. The extent to what these variables are met shall no doubt affects the effectiveness of any sports development. Two distinguishing features of the Nigerian sports system are its central organization and its employment for specific socio-political objectives, it is against this backdrop that this paper will x-ray the politicization of sports which parallels sports development in the enhanced role of sports and in contrast with developed nations system and management.

Keywords: sport development, sport policy, personnel, program, facilities, funding, sponsorship

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Authors: Meriem Boukais, B. Dennai, A. Ould- Abbas

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The efficiency of SiGe solar cells might be improved by a wide-band-gap window layer. In this work we were simulated using the one dimensional simulation program called analysis of microelectronic and photonic structures (AMPS-1D). In the modeling, the thickness of silicon window was varied from 80 to 150 nm. The rest of layer’s thicknesses were kept constant, by varying thickness of window layer the simulated device performance was demonstrate in the form of current-voltage (I-V) characteristics and quantum efficiency (QE).

Keywords: modeling, SiGe, AMPS-1D, quantum efficiency, conversion, efficiency

Procedia PDF Downloads 727

Authors: Chiu-Neng Su, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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In lithium-ion batteries (LIBs) the solid–electrolyte interphase (SEI) layer, which forms on the anode surface, plays a crucial role in stabilizing battery performance. Over the past two decades, efforts to enhance LIB electrolytes have primarily focused on refining the quality of SEI components. Despite these endeavors, several observed phenomena remain inadequately improved the SEI layer. Consequently, there has been a significant surge in research interest regarding the behavior of electrolyte solvation structures to elucidate improvements in battery performance. Thus, in this study, we aimed to explore the solvation structures of LiPF₆ in a mixture of organic solvents, tetrahydrofuran (THF) and 2-methyl-tetrahydrofuran (MTHF) using ab-initio molecular dynamics (AIMD) simulations. Our work investigated the solvation structure of electrolytes with different salt concentrations: low-concentration electrolyte (1.0M LiPF6 in 1:1v/v mixture of THF and MTHF), and high-concentration electrolyte (2.0M LiPF₆ in 1:1v/v mixture of THF and MTHF) and compared them with that of conventional electrolyte (1.0M LiPF₆ in 1:1v/v mixture of ethylene carbonate (EC) and dimethyl carbonate (DMC)). Furthermore, the reduction stability of Li+ solvation structures in these electrolyte systems are investigated. It is found that the first solvation shell of Li+ primary consists of THF. We also analyzed the molecular orbital energy levels to understand the reducing stability of these solvents. Compared with the solvation sheath of commercial electrolyte, the THF/MTHF-containing electrolytes have a higher lowest unoccupied molecular orbital (LUMO) energy level, resulting in improved reduction and interface stability. It has been shown that Li-Al alloy can significantly improve cycle life and promote the formation of a dense SEI layer. Therefore, this study aims to construct the solvation structures obtained from calculations of the pure electrolyte system on the surface of Al-Li alloy. Additionally, AIMD simulations will be conducted to investigate chemical reactions at the interface. This investigation aims to elucidate the composition of the SEI layer formed. Furthermore, Bader charges are used to determine the origin and flow of electrons, thereby revealing the sequence of reduction reactions for generating SEI layers.

Keywords: lithium, aluminum, alloy, battery, solvation structure

Procedia PDF Downloads 30

Authors: S. J. Bindhu, Edwina G. Rodrigues, Jijo Balakrishnan

Abstract:

A grid-connected photovoltaic (PV) micro inverter with good performance properties is proposed in this paper. The proposed inverter with a quadrupler, having more efficiency and less voltage stress across the diodes. The stress that come across the diodes that use in the inverter section is considerably low in the proposed converter, also the protection scheme that we provided can eliminate the chances of the error due to fault. The proposed converter is implemented using perturb and observe algorithm so that the fluctuation in the voltage can be reduce and can attain maximum power point. Finally, some simulation and experimental results are also presented to demonstrate the effectiveness of the proposed converter.

Keywords: DC-DC converter, MPPT, quadrupler, PV panel

Procedia PDF Downloads 846