Search results for: C. Prakash Chandra Joshua

Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Bikas Chandra Bhattarai

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Child labour is the serious issue all over the world. In Nepal, many children are working in different structured and unstructured sector. Metal fabrication is one of the sectors where many children are involved. The present study is carried out to focus on the overall socio-economic condition, psychological aspect, working environment condition and welfare of the child labour. Metal fabrication factories from Kirtipur, Chovar Area, Gongabu, Sitapaila and Sankhamul area of Kathmandu municipality were selected for the study. The structured questionnaire was prepared, and overall 55 children under age 16 were interviewed. Working in metal fabrication factory is risky job for children. The main reason behind child labour is poverty. The working environment in the metal fabrication factory was not found satisfactory. Children are exposed to various types of physical and chemical hazards. Factories are not paying proper attention to safety condition at the workplace. Large number of children is attracted towards smoking and drinking alcohol leading to unnecessary expense of their income. There should be the provision of regular health check up and insurance to the working children. Monitoring from the government level should be implemented for the betterment of working children.

Keywords: child labour, Kathmandu, Nepal, metal fabrication

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Authors: Arya Prakash Padhi, Anupam Chakrabarti, Rajib Chowdhury

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Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved.

Keywords: 3D generative adversarial network, deep learning, structural topology optimization, variational auto encoder

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Authors: Geeta Sharma, Suma Chandra

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Sugarcane is one of the major commercial crop playing roles in agriculture and industrial economy of India. Globally sugarcane is affected by approximately 240 diseases caused by various plant pathogenic organisms. Among them, red rot disease caused by the fungus Colletotrichum falcatum, is one of the most important diseases. In the present investigation, one fungal bioagent of Trichoderma harzianum, Pant Bioagent 1 and one bacterial bioagent Pseudomonas fluorescence, Pant Bioagent 2 (PBAT 1 and PBAT 2, respectively) were tested by dual culture method against the pathogen under laboratory conditions. The effectiveness of biocontrol agents was observed against four isolates of C. falcatum. In the case of PBAT1 maximum percent inhibition of pathogen was recorded in isolated Cf 0238 (61.05%), followed by Cf 09 (60.62%) whereas, minimum percent inhibition was recorded in Cf 3220 (48.55%) and in case of PBAT2 maximum mycelial growth inhibition percent was recorded in Cf 767 (50.50%) followed by Cf 088230(48.83%), whereas minimum percent inhibition was recorded in Cf 08 (40.16%) followed by Cf 0238 (41.83%). The present study showed that these biocontrol agents have the potential of controlling the pathogen and can further be used for the management of red rot disease in field.

Keywords: biocontrol agents, Colletotrichum falcatum, isolates, sugarcane

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Authors: A. Calvin Antony, Sakthi Kumar Arul Prakash, V. R. Sanal Kumar

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In this paper a unique alpha-beta double piston 'stirling engine' is designed, manufactured and conducted laboratory test to ameliorate the efficiency of the stirling engine. The paper focuses on alpha and beta type engines, capturing their benefits and eradicating their short comings; along with the output observed from the flywheel. In this model alpha engine is kinematically with a piston cylinder arrangement which works quite like a beta engine. The piston of the new cylinder is so designed that it replicates a glued displacer and power piston as similar to that of beta engine. The bigger part of the piston is the power piston, which has a gap around it, while the smaller part of the piston is tightly fit in the cylinder and acts like the displacer piston. We observed that the alpha-beta double piston stirling engine produces 25% increase in power compare to a conventional alpha stirling engine. This working model is a pointer towards for the design and development of an alpha-beta double piston Stirling engine for industrial applications for producing electricity from the heat producing exhaust gases.

Keywords: alpha-beta double piston stirling engine , alpha stirling engine , beta double piston stirling engine , electricity from stirling engine

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Authors: Sai Chand, Ashish Dhamaniya, Satish Chandra

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Curbside bus stops are provided on urban roads when sufficient land is not available to construct bus bays. The present study demonstrates the effect of curbside bus stops on midblock capacity of an urban arterial road. Data were collected on seven sections of 6-lane urban arterial roads in New Delhi. Three sections were selected without any side friction to estimate the base value of capacity. Remaining four sections were with curbside bus stop. Speed and volume data were collected in field and these data were used to estimate the capacity of a section. The average base midblock capacity of a 6–lane divided urban road was found to be 6314 PCU/hr which was further referred as base capacity. Effect of curbside bus stop on midblock capacity of urban road was evaluated by comparing the capacity of a section with curbside bus stop with that of the base capacity. Finally, a mathematical relation has been developed between bus frequency and capacity loss. Also a relation has been suggested between dwell time and capacity loss. The developed relations would be very useful for practising engineers to estimate capacity loss due to bus stop.

Keywords: bus frequency, bus stops, capacity loss, urban arterial

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Authors: Joshua Paul Steimel, Michael Pappas, Ethan Hall

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Particle-particle interactions are critical in determining the state of an active matter system. Unique and ubiquitous non-equilibrium behavior like swarming, vortexing, spiraling, and much more is governed by interactions between active units or particles. In hybrid active-passive matter systems, the attraction between spinning active units in a 2D monolayer of passive particles is controlled by the mechanical behavior of the passive monolayer. We demonstrate here that the range and dynamics of this attraction can be controlled by changing the composition of the passive monolayer by adding dopant passive particles. These dopant passive particles effectively pin the movement of dislocation motion in the passive media and reduce the probability of defect motion required to erode the bridge of passive particles between active spinners, thus reducing the range of attraction. Additionally, by adding an out of plane component to the magnetic moment and creating a top-like motion a short range repulsion emerges between the top-like particle. At inter-top distances less than four particle diameters apart, the tops repel but beyond that, distance attract up to 13 particle diameters apart. The tops were also able to locally and transiently anneal the passive monolayer. Thus we demonstrate that by tuning several parameters of the hybrid active matter system, one can observe very different emergent behavior.

Keywords: active matter, colloids, ferromagnetic, annealing

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Authors: Gopal Ji, Priyanka Dwivedi, Shanthi Sundaram, Rajiv Prakash

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Inhibition effect of aqueous Argemone Mexicana root extract (AMRE) on mild steel corrosion in 1 M HCl has been studied by weight loss, Tafel polarization curves, electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. Results indicate that inhibition ability of AMRE increases with the increasing amount of the extract. A maximum corrosion inhibition of 94% is acknowledged at the extract concentration of 400 mg L-1. Polarization curves and impedance spectra reveal that both cathodic and anodic reactions are suppressed due to passive layer formation at metal-acid interface. It is also confirmed by SEM micro graphs and FTIR studies. Furthermore, the effects of acid concentration (1-5 M), immersion time (120 hours) and temperature (30-60˚C) on inhibition potential of AMRE have been investigated by weight loss method and electrochemical techniques. Adsorption mechanism is also proposed on the basis of weight loss results, which shows good agreement with Langmuir isotherm.

Keywords: mild steel, polarization, SEM, acid corrosion, EIS, green inhibition

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Authors: Joshua N. Edokpayi, John O. Odiyo, Titus A. M. Msagati, Elizabeth O. Popoola

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Polycyclic aromatic hydrocarbons (PAHs) are very toxic and persistent environmental contaminants. This study was undertaken to assess the concentrations and possible sources of 16 PAHs classified by the United State Environmental Protection Agency as priority pollutants in Mvudi and Nzhelele Rivers and sediments. Effluents from Thohoyandou wastewater treatment plant and Siloam waste stabilization ponds were also investigated. Diagnostic ratios were used to evaluate the possible sources of PAHs. PAHs in the water samples were extracted using 1:1 dichloromethane and n-hexane mixtures, while those in the sediment samples were extracted with 1:1 acetone and dichloromethane using ultrasonication method. The extracts were purified using SPE technique and reconstituted in n-hexane before analyses with GC-TOF-MS. The results obtained indicate the prevalence of high molecular weight PAHs in all the samples. PAHs concentrations in water and sediment samples from all the sampling sites were in the range of 13.174-26.382 mg/L and 27.10-55.93 mg/kg, respectively. Combustion of biomass was identified as the major possible source of PAHs. Effluents from wastewater treatment facilities were also considered as major anthropogenic contributions to the levels of PAHs determined in both river waters and sediments. Mvudi and Nzhelele Rivers show moderate to high contamination level of PAHs.

Keywords: polycyclic aromatic hydrocarbon, rivers, sediments, wastewater effluents

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Authors: Junnile Romero, Ilhwan Park, Vannie Joy Resabal, Carlito Tabelin, Richard Alorro, Leaniel Silva, Joshua Zoleta, Takunda Mandu, Kosei Aikawa, Mayumi Ito, Naoki Hiroyoshi

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Rare earth elements (REE) play a vital role in technological advancement due to their unique physical and chemical properties essential for various renewable energy applications. However, this increasing demand represents a challenging task for sustainability that corresponds to various research interests relating to the development of various extraction techniques, particularly on the extractant being used. In this study, TK221 (a modified polymer resin containing diglycolamide, carbamoyl methyl phosphine oxide (CMPO), and diglycolamide (DGA-N)) has been investigated as a conjugate extractant. FTIR and SEM analysis results confirmed the presence of CMPO and DGA-N being coated onto the PS-DVB support of TK221. Moreover, the kinetic rate law and adsorption isotherm batch test was investigated to understand the corresponding adsorption mechanism. The results show that REEs’ (Nd, Y, Ce, and Er) obtained pseudo-second-order kinetics and Langmuir isotherm, suggesting that the adsorption mechanism undergoes a single monolayer adsorption site via a chemisorption process. The Qmax values of Nd, Ce, Er, Y, and Fe were 45.249 mg/g, 43.103 mg/g, 35.088 mg/g, 15.552 mg/g, and 12.315 mg/g, respectively. This research further suggests that TK221 polymer resin can be used as an alternative absorbent material for an effective REE extraction.

Keywords: rare earth element, diglycolamide, characterization, extraction resin

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Authors: Joshua Bradley, Matthew Buns

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This study aimed to identify the effect of concurrent nutritional supplementation on soccer performance as players ingested either carbohydrate CHO (52 g of Cytocarb Maltodextrin) or a combined carbohydrate and protein PRO (Muscle Milk Pro Series 17g CHO + 50 g PRO liquid) supplement. Twelve male, junior college soccer players (age: 18 ± 6 years, wt. 73.3 ± 8.6 kg) completed three trials wearing global positioning systems (GPS) to measure total running distance and sprinting distance during soccer simulation games. The first match simulation was a baseline match with no supplementation. One hour prior to the second match, simulation players were randomly assigned to one of two supplemental groups CHO or CHO + PRO. A repeated measures ANOVA with a Greenhouse-Geisser correction revealed a statistically significant increase in the total distance run for the CHO supplementation group in comparison to the CHO + PRO group (10.19 ± .200 km vs. 9.77± .194km, p = .035). Although the total running distance was meaningfully influenced by the supplementation, the pattern of response for total sprinting distance was not influenced by supplementation. There was a decline in sprinting distance and total running distance from first half to second half, both for the control (M = -0.01 km, SD = 0.17) and CHO supplementation group (-0.04 km, SD = .19), although these differences were not statistically meaningful. There was a positive correlation between sprinting distance and total distance, which was statistically significant (r = -.514, n = 36, p = .01) In conclusion, supplementation influenced the pattern of activity and demonstrated between-trial differences.

Keywords: GPS, nutrition, simulation, supplementation

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Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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Authors: Saroj Poudel, Joshua Mancini, Douglas Pike, Jennifer Timm, Alexei Tyryshkin, Vikas Nanda, Paul Falkowski

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On the early Earth, protein-metal complexes likely harvested energy from a reduced environment. These complexes would have been precursors to the metabolic enzymes of ancient organisms. Hydrogenase is an essential enzyme in most anaerobic organisms for the reduction and oxidation of hydrogen in the environment and is likely one of the earliest evolved enzymes. To attempt to reinvent a precursor to modern hydrogenase, we computationally designed a short thirteen amino acid peptide that binds the often-required catalytic transition metal Nickel in hydrogenase. This simple complex can achieve hundreds of hydrogen evolution cycles using light energy in a broad range of temperature and pH. Biophysical and structural investigations strongly indicate the peptide forms a di-nickel active site analogous to Acetyl-CoA synthase, an ancient protein central to carbon reduction in the Wood-Ljungdahl pathway and capable of hydrogen evolution. This work demonstrates that prior to the complex evolution of multidomain enzymes, early peptide-metal complexes could have catalyzed energy transfer from the environment on the early Earth and enabled the evolution of modern metabolism

Keywords: hydrogenase, prebiotic enzyme, metalloenzyme, computational design

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Authors: Sameena Malik, Ghosh Prakash, Sandeep Mudliar, Vishal Waindeskar, Atul Vaidya

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In this study, the biodegradability enhancement along with COD color and toxicity removal of pharmaceutical effluent by O₃, O₃/Fe²⁺, O₃/nZVI processes has been evaluated. The nZVI particles were synthesized and characterized by XRD and SEM analysis. Kinetic model was reasonably developed to select the ozone doses to be applied based on the ozonation kinetic and mass transfer coefficient values. Nano catalytic ozonation process (O₃/nZVI) effectively enhanced the biodegradability (BI=BOD₅/COD) of pharmaceutical effluent up to 0.63 from 0.18 of control with a COD, color and toxicity removal of 62.3%, 93%, and 75% respectively compared to O₃, O₃/Fe²⁺ pretreatment processes. From the GC-MS analysis, 8 foremost organic compounds were predominantly detected in the pharmaceutical effluent. The disappearance of the corresponding GC-MS spectral peaks during catalyzed ozonation process indicated the degradation of the effluent. The changes in the FTIR spectra confirms the transformation/destruction of the organic compounds present in the effluent to new compounds. Subsequent aerobic biodegradation of pretreated effluent resulted in biodegradation rate enhancement by 5.31, 2.97, and 1.22 times for O₃, O₃/Fe²⁺ and O₃/nZVI processes respectively.

Keywords: iron nanoparticles, pharmaceutical effluent, ozonation, kinetics, mass transfer

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Authors: Rajesh Kondareddy, Prakash Kumar Nayak, Maunash Das, Vrinatri Velentina Boro

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Today, there is a huge global concern for sustainable development which would include minimizing the consumption of non-renewable energies without affecting the basic global economy. Solar drying is one of the important processes used for extending the shelf life of agricultural products. The performance of a low cost automated solar dryer fitted with cascade control scheme and modified PI controller for drying chilli was investigated. The dryer was composed of designed solar collector (air heater) fitted with cylindrical pipes to improve the air velocity and a solar drying chamber containing rack of two cheese cloth (net) trays both being integrated together. The air allowed in through air inlet is heated up in the solar collector and channelled through the drying chamber where it is utilized in drying (removing the moisture content from the food substance or agricultural produce loaded). Here, to maintain the temperature in the heating chambers and to improve performance, a modified PI (Proportional–Integral) controller was used due its simplicity and robustness. Drying time for drying chilli from the initial moisture content of 88.5% (wb) to 7.3% (wb) was estimated to be 14 hours in solar dryer whereas 32 h was observed in the open sun drying.

Keywords: cascade control, chilli, PI controller, solar dryer

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Authors: Joseph C. Chen, Joshua Cox

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This research focuses on the use of the Taguchi method to reduce the surface roughness and improve dimensional accuracy of parts machined by Wire Electrical Discharge Machining (EDM) with S7 heat treated steel material. Due to its high impact toughness, the material is a candidate for a wide variety of tooling applications which require high precision in dimension and desired surface roughness. This paper demonstrates that Taguchi Parameter Design methodology is able to optimize both dimensioning and surface roughness successfully by investigating seven wire-EDM controllable parameters: pulse on time (ON), pulse off time (OFF), servo voltage (SV), voltage (V), servo feed (SF), wire tension (WT), and wire speed (WS). The temperature of the water in the Wire EDM process is investigated as the noise factor in this research. Experimental design and analysis based on L₁₈ Taguchi orthogonal arrays are conducted. This paper demonstrates that the Taguchi-based system enables the wire EDM process to produce (1) high precision parts with an average of 0.6601 inches dimension, while the desired dimension is 0.6600 inches; and (2) surface roughness of 1.7322 microns which is significantly improved from 2.8160 microns.

Keywords: Taguchi Parameter Design, surface roughness, Wire EDM, dimensional accuracy

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Authors: Chakshu Baweja, Ishaan Prakash, Deepak Giri, Prithwish Mukherjee, Herambraj Ashok Nalawade

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The need to prevent and control rampant and indiscriminate usage of energy in present-day realm on earth has motivated active research efforts aimed at understanding of controlling mechanisms leading to sustained energy. Although much has been done but complexity of the problem has prevented a complete understanding due to nonlinear interaction between flow, heat and mass transfer in terrestrial environment. Therefore, there is need for a systematic study to clearly understand mechanisms controlling energy-spreading phenomena to increase a system’s efficiency. The present work addresses the issue of sustaining energy and proposes a devoted technique of optimizing energy in the automotive domain. The proposed method focus on utilization of the mechanical and thermal energy of an automobile IC engine by converting and storing energy due to motion of a piston in form of electrical energy. The suggested technique utilizes piston motion of the engine to generate high potential difference capable of working as a secondary power source. This is achieved by the use of a gear mechanism and a flywheel.

Keywords: internal combustion engine, energy, electromagnetic induction, efficiency, gear ratio, hybrid vehicle, engine shaft

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Authors: Gopikrishnan, Bharathiraja, Boopalan, Jensin Joshua

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The Pitot static tube has proven their values and practicability in measuring velocity of fluids for many years. With the aim of extensive usage of such Pitot tube systems, one of the major enabling technologies is to use the design and fabricate a high sensitive pitot tube for the purpose of calibration of the subsonic wind tunnel. Calibration of wind tunnel is carried out by using different instruments to measure variety of parameters. Using too many instruments inside the tunnel may not only affect the fluid flow but also lead to drag or losses. So, it is essential to replace the different system with a single system that would give all the required information. This model of high sensitive Pitot tube has been designed to ease the calibration process. It minimizes the use of different instruments and this single system is capable of calibrating the wind tunnel test section. This Pitot static tube is completely digitalized and so that the velocity data`s can be collected directly from the instrument. Since the turbulence factors are dependent on velocity, the data’s that are collected from the pitot static tube are then processed and the level of turbulence in the fluid flow is calculated. It is also capable of measuring the pressure distribution inside the wind tunnel and the flow angularity of the fluid. Thus, the well-designed high sensitive Pitot static tube is utilized in calibrating the tunnel and also for the measurement of turbulence.

Keywords: pitot static tube, turbulence, wind tunnel, velocity

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Authors: Muhammad Faizan Butt, Maria Ambreen Tahir, Joshua James Pilkington, A. A. Warsi

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Background: Total parenteral nutrition (TPN) use within the NHS is crucial in the prevention of malnourishment. TPN prescriptions are tailored to an individual patient’s needs. TPN bags come in fixed sizes, and minimizing wastage has financial and sustainability implications for the health service. The aim of the study is to assess current prescribing practices, look at the volume of TPN wastage and identify reasons for it. Methodology: A retrospective cohort study on TPN prescriptions over a period of 1 year (Jan-Dec 2022) was performed. All patients prescribed TPN that had been admitted under a general surgery consultant in a small district hospital were included. Data were extracted from hospital electronic records and dietician charts. Data were described, and reasons for TPN wastage were explored. Results: 49 patients were identified. The average length of TPN prescription was 8 days (median). This totaled 608 prescriptions. Of the bags prescribed, 258, 169, and 181 were 10g (2500ml), 14g (2000ml), and 18g (2000ml), respectively. The mean volume wasted from each type of bag was 634ml, 634ml, and 648ml, respectively. Reasons for TPN wastage identified were: no loss (25%), smaller bags not available (53.6%), step-down regime (8.1%), and other (12.2%). Conclusion: This study has identified that the current stocking and prescribing of TPN within a district general hospital leads to a significant wastage of 638.2ml (average). The commonest reason for wastage is the non-availability of a more appropriate sized bag.

Keywords: general surgery, TPN, sustainability, wastage

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Authors: Rajesh Chandra, Uttam K. Ghosh

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This study demonstrates microalgal bio-diesel generation from a cheap, abundant, non-edible fruit pulp of Cassia fistula L. The Cassia fistula L. fruit pulp aqueous extract (CFAE) was utilized as a growth medium for cultivation of microalga Chlorella minutissima (C. minutissima). This microalga accumulated a high amount of lipids when cultivated with CFAE as a source of nutrition in comparison to BG-11 medium. Different concentrations (10, 20, 30, 40 and 50%) of CFAE diluted with distilled water were used to cultivate microalga. Effects of light intensity and photoperiod were also observed on biomass and lipid yield of microalga. Light intensity of 8000 lux with a photoperiod of 18 h resulted in maximum biomass and lipid yield of 1.28 ± 0.03 and 0.3968 ± 0.05 g/L, respectively when cultivated with 40% CFAE. Fatty acid methyl ester (FAME) profile of bio-diesel obtained shown the presence of myristic acid (C14:0), palmitic acid (C16:0), palmitoleic acid (C16:1), stearic acid (C18:0), linoleic acid (C18:2), linolenic acid (C18:3), arachidic acid (C20:0), and gondoic acid (C20:1), as major fatty acids. These facts reflect that the fruit pulp of Cassia fistula L. can be used for cultivation of C. minutissima.

Keywords: biomass, bio-diesel, Cassia fistula L., C. minutissima, GC-MS, lipid

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Tonny Ograh, Joshua Ayarkwa, Dickson Osei-Asibey, Alex Acheampong, Peter Amoah

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Theories are used to improve the conceptualization of research ideas. These theories enhance valuable elucidations that help us to grasp the meaning of research findings. Nevertheless, the use of theories to promote studies in green supplier selection in procurement decisions has attracted little attention. With the emergence of sustainable procurement, public procurement practitioners in Ghana are yet to achieve relevant knowledge on green supplier selections due to insufficient knowledge and inadequate appropriate frameworks. The flagrancy of the consequences of public procurers’ failure to integrate environmental considerations into supplier selection explains the adoption of a multi-theory approach for comprehension of the dynamics of green integration into supplier selection. In this paper, the practicality of three theories for improving the understanding of the influential factors enhancing the integration of environmental sustainability into supplier selection was reviewed. The three theories are Resource-Based Theory, Human Capital Theory and Absorptive Capacity Theory. This review uncovered knowledge management, top management commitment, and environmental management capabilities as important elements needed for the integration of environmental sustainability into supplier selection in public procurement. The theoretical review yielded a framework that conceptualizes knowledge and capabilities of practitioners relevant to the incorporation of environmental sustainability into supplier selection in public procurement.

Keywords: environmental, sustainability, supplier selection, environmental procurement, sustainable procurement

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Authors: Pravin Gaikwad, Prakash Mahanwar

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The main objective of incorporating natural fibers such as Henequen microfibers (NF) into the High-Density Polyethylene (HDPE) polymer matrix is to reduce the cost and to enhance the mechanical as well as other properties. The Henequen microfibers were chopped manually to 5-7mm in length and added into the polymer matrix at the optimized concentration of 8 wt %. In order to facilitate the link between Henequen microfibers (NF) and HDPE matrix, coupling agent such as Glycidoxy (Epoxy) Functional Methoxy Silane (GPTS) at various concentrations from 0.1%, 0.3%, 0.5%, 0.7%, 0.9%, and 1% by weight to the total fibers were added. The tensile strength of the composite increased marginally while % elongation at break of the composites decreased with increase in silane loading by wt %. Tensile modulus and stiffness observed increased at 0.9 wt % GPTS loading. Flexural as well as impact strength of the composite decreased with increase in GPTS loading by weight %. Dielectric strength of the composite also found increased marginally upto 0.5wt % silane loading and thereafter remained constant.

Keywords: Henequen microfibers (NF), polymer composites, HDPE, coupling agent, GPTS

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Authors: Joshua Ikpimi, Dimeji Abe, Nonso Okoye, Gideon Ikpimi, Prince Idemudia

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Training programmes are integral parts of development for employees to develop themselves and also to develop the organisation. Lack of training and inadequate training adversely affect the productivity in any organisation. Lack of training in the water sector can impair development and improper management of water. Training programs are given to water professionals, especially in a developing country like South Africa, to perform well in their day to day activities. The aim of this study was to evaluate the current training program in place for water professionals at KwaZulu Natal province of South Africa. The objectives were to determine the training programs that are suitable for their job descriptions and to determine the gaps with the training programs and to make recommendations on ways to improve the training programs. This study is a quantitative study which enabled an evaluation of training programs for KwaZulu Natal water professionals. The sample population was 120 professionals across all the cities and towns in KwaZulu Natal province. The water professionals were evaluated using structured questionnaire distributed to the respondents from September to December 2017. The data was analysed using R software. The study found that province has training programs that are valuable for their water professionals. However, involvement of some professionals in administrative activities was hindered by some inappropriate training. Many areas of improvement are suggested to the province in training its water professionals. Training was found to improve performance, commitment, motivation and staff retention of water professionals in the province.

Keywords: KwaZulu Natal, performance, training, water

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Authors: James Adewale, Joshua Sunday

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In this paper, we developed a linear multistep method, which is implemented in predictor corrector-method. The corrector is developed by method of collocation and interpretation of power series approximate solutions at some selected grid points, to give a continuous linear multistep method, which is evaluated at some selected grid points to give a discrete linear multistep method. The predictors were also developed by method of collocation and interpolation of power series approximate solution, to give a continuous linear multistep method. The continuous linear multistep method is then solved for the independent solution to give a continuous block formula, which is evaluated at some selected grid point to give discrete block method. Basic properties of the corrector were investigated and found to be zero stable, consistent and convergent. The efficiency of the method was tested on some linear, non-learn, oscillatory and stiff problems of first order, initial value problems of ordinary differential equations. The results were found to be better in terms of computer time and error bound when compared with the existing methods.

Keywords: predictor, corrector, collocation, interpolation, approximate solution, independent solution, zero stable, consistent, convergent

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Authors: Raghav Lakhotia, Chandra Kanth Nagesh, Krishna Madgula

Abstract:

A lot has been said and discussed regarding the rationale and significance of the Bechdel Score. It became a digital sensation in 2013, when Swedish cinemas began to showcase the Bechdel test score of a film alongside its rating. The test has drawn criticism from experts and the film fraternity regarding its use to rate the female presence in a movie. The pundits believe that the score is too simplified and the underlying criteria of a film to pass the test must include 1) at least two women, 2) who have at least one dialogue, 3) about something other than a man, is egregious. In this research, we have considered a few more parameters which highlight how we represent females in film, like the number of female dialogues in a movie, dialogue genre, and part of speech tags in the dialogue. The parameters were missing in the existing criteria to calculate the Bechdel score. The research aims to analyze 342 movies scripts to test a hypothesis if these extra parameters, above with the current Bechdel criteria, are significant in calculating the female representation score. The result of the Principal Component Analysis method concludes that the female dialogue content is a key component and should be considered while measuring the representation of women in a work of fiction.

Keywords: Bechdel test, dialogue genre, parts of speech tags, principal component analysis

Procedia PDF Downloads 100

Authors: Gbenga F. Akomolafe, Joseph Omojola, Ezekiel S. Joshua, Seyi C. Adediwura, Elijah T. Adesuji, Michael O. Odey, Oyinade A. Dedeke, Ayo H. Labulo

Abstract:

Microgravity is known to be a major abiotic stress in space which affects plants depending on the duration of exposure. In this work, tomatoes seeds were exposed to long hours of simulated microgravity condition using a one-axis clinostat. The seeds were sown on a 1.5% combination of plant nutrient and agar-agar solidified medium in three Petri dishes. One of the Petri dishes was mounted on the clinostat and allowed to rotate at the speed of 20 rpm for 72 hours, while the others were subjected to the normal gravity vector. The anatomical sections of both clinorotated and normal gravity plants were made after 72 hours and observed using a Phase-contrast digital microscope. The percentage germination, as well as the growth rate of the normal gravity seeds, was higher than the clinorotated ones. The germinated clinorotated roots followed different directions unlike the normal gravity ones which grew towards the direction of gravity vector. The clinostat was able to switch off gravistimulation. Distinct cellular arrangement was observed for tomatoes under normal gravity condition, unlike those of clinorotated ones. The root epidermis and cortex of normal gravity are thicker than the clinorotated ones. This implied that under long-term microgravity influence, plants do alter their anatomical features as a way of adapting to the stress condition.

Keywords: anatomy, clinostat, germination, lycopersicon esculentum, microgravity

Procedia PDF Downloads 289

Authors: Joshua Harrell, Gideon Osei Bonsu, Susan Garza, Clarence Conner, Da’Neisha Harris, Emma Bukoswki, Zohreh Safari

Abstract:

The Social Vulnerability Index (SVI) stands as a pivotal tool for gauging community resilience amidst diverse stressors, including pandemics like COVID-19. This paper synthesizes recent research and underscores the significance of SVI in elucidating the differential impacts of crises on communities. Drawing on studies by Fox et al. (2023) and Mah et al. (2023), we delve into the application of SVI alongside emerging data sources to uncover nuanced insights into community vulnerability. Specifically, we explore the utilization of SVI in conjunction with mobility data from platforms like SafeGraph to probe the intricate relationship between social vulnerability and mobility dynamics during the COVID-19 pandemic. By leveraging 16 community variables derived from the American Community Survey, including socioeconomic status and demographic characteristics, SVI offers actionable intelligence for guiding targeted interventions and resource allocation. Building upon recent advancements, this paper contributes to the discourse on harnessing AI techniques to mitigate health disparities and fortify public health resilience in the face of pandemics and other crises.

Keywords: social vulnerability index, mobility dynamics, data analytics, health equity, pandemic preparedness, targeted interventions, data integration

Procedia PDF Downloads 32

Authors: Prakash Singh

Abstract:

For schools to be desirable places in which to work, it is necessary for principals to recognise their teachers’ emotions, and be sensitive to their needs. This necessitates that principals are capable to correctly identify their emotionally intelligent behaviours (EIBs) they need to use in order to be successful leaders. They also need to have knowledge of their emotional intelligence and be able to identify the factors and situations that evoke emotion at an interpersonal level. If a principal is able to do this, then the control and understanding of emotions and behaviours of oneself and others could improve vastly. This study focuses on the interpersonal EIBS of principals affecting the job satisfaction of teachers. The correlation coefficients in this quantitative study strongly indicate that there is a statistical significance between the respondents’ level of job satisfaction, the rating of their principals’ EIBs and how they believe their principals’ EIBs will affect their sense of job satisfaction. It can be concluded from the data obtained in this study that there is a significant correlation between the sense of job satisfaction of teachers and their principals’ interpersonal EIBs. This means that the more satisfied a teacher is at school, the more appropriate and meaningful a principal’s EIBs will be. Conversely, the more dissatisfied a teacher is at school the less appropriate and less meaningful a principal’s interpersonal EIBs will be. This implies that the leaders’ EIBs can be construed as one of the major factors affecting the job satisfaction of employees.

Keywords: emotional intelligence, teachers' emotions, teachers' job satisfaction, principals' emotionally intelligent behaviours

Procedia PDF Downloads 446