Search results for: classification efficiency

Authors: Bianca W. O. Silva, Adriana C. M. Andrade, Gustavo C. M. Lucena, Virna M. S. Lima

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Introduction: Basic life support (BLS) involves the immediate recognition of cardiopulmonary arrest. Each year, 359.400 and 275.000 individuals with cardiac arrest are attended in emergency departments in USA and Europe. Brazilian data shows that 200.000 cardiac arrests occur every year, and half of them out of the hospital. Medical schools around the world teach BLS in the first years of the course, but studies show that there is a decline of the knowledge as the years go by, affecting the chain of survival. The objective was to analyze the knowledge of medical students about BLS and the retention of this learning throughout the course. Methods: This study included 150 students who were at the second and third year of a medical school in Salvador, Bahia, Brazil. The instrument of data collection was a structured questionnaire composed of 20 questions based on the 2015 American Heart Association guideline. The Pearson Chi-square test was used in order to study the association between previous training, sex and semester with the degree of knowledge of the students. The Kruskal-Wallis test was used to evaluate the different yields obtained between the various semesters. The number of correct answers was described by average and quartiles. Results: Regarding the degree of knowledge, 19.6% of the female students reached the optimal classification, a better outcome than the achieved by the male participants. Of those with previous training, 33.33% were classified as good and optimal, none of the students reached the optimal classification and only 2.2% of them were classified as bad (those who did not have 52.6% of correct answers). The analysis of the degree of knowledge related to each semester revealed that the 5th semester had the highest outcome: 30.5%. However, the acquaintance presented by the semesters was generally unsatisfactory, since 50% of the students, or more, demonstrated knowledge levels classified as bad or regular. When confronting the different semesters and the achieved scores, the value of p was 0.831. Conclusion: It is important to focus on the training of medical professionals that are capable of facing emergency situations, improving the systematization of care, and thereby increasing the victims' possibility of survival.

Keywords: basic life support, cardiopulmonary ressucitacion, education, medical students

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Authors: Siqi Lin, Yangang Zhao

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Concrete-filled steel tube column achieves the excellent performance of high strength, stiffness, and ductility due to the confinement from the steel tube. Well understanding the stress of the steel tube is important to make clear the confinement effect. In this paper, the ultimate stress of the steel tube in circular concrete-filled steel tube columns subjected to axial compression was studied. Experimental tests were conducted to investigate the effects of the parameters, including concrete strength, steel strength, and D/t ratio, on the ultimate stress of the steel tube. The stress of the steel tube was determined by employing the Prandtl-Reuss flow rule associated with isotropic strain hardening. Results indicate that the stress of steel tube was influenced by the parameters. Specimen with higher strength ratio fy/fc and smaller D/t ratio generally leads to a higher utilization efficiency of the steel tube.

Keywords: concrete-filled steel tube, axial compression, ultimate stress, utilization efficiency

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Authors: Chaudhary Archana, Dhingra Poshika

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The architecture of the world is at a crossroads with the advent of new technology. The issues of energy efficiency and global warming are getting important with the coming times. New technologies are making their mark. For the architecture profession, nanotechnology will greatly impact construction materials and their properties. Nanotechnology, the understanding and control of matter at a scale of one to one hundred billions of a meter, is bringing incredible changes to the materials and processes of buildings. Materials will behave in many different ways as we are able to more precisely control their properties at the nanoscale. It is precisely called the next industrial revolution. We live in an age where scientific progress continues to transform human lifestyle. This is evermore true when it comes to the progress being made in the field of nanotechnology. This science stands to change and advance the practice of design in a multitude of ways – where architectural progress is being made at the molecular level. The nanotechnology has already been adopted in various buildings across the world. What an impact it shall have on the futuristic architecture in Chandigarh, India shall be discussed in the paper. But before we hurtle off toward a nano-utopia, we need to step back and ask ourselves whether this is a direction in which we really want to go.

Keywords: building materials, energy efficiency, nanotechnology, sustainability

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Authors: Adrian Garrido Sanchis, Richard Pashley

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The MS2 (ATCC15597-B1) virus was used as a surrogate to estimate the inactivation rates for enteric viruses when using a hot air bubble column evaporator (HBCE) system in the treatment of household wastewater. In this study, we have combined MS2 virus surface charging properties with thermal inactivation rates, using an improved double layer plaque assay technique, in order to assess the efficiency of the HBCE process for virus removal in water. When bubbling a continuous flow of dry air, at 200°C, only heats the aqueous solution in the bubble column to about 50°C. Viruses are not inactivated by this solution temperature, as confirmed separately from water bath heating experiments. Hence, the efficiency of the HBCE process for virus removal in water appeared to be caused entirely by collisions between the hot air bubbles and the virus organisms. This new energy efficient treatment for water reuse applications can reduce the thermal energy required to only 25% (about 113.7 kJ/L) of that required for boiling (about 450 kJ/L).

Keywords: MS2 virus inactivation, water reuse, hot bubble column evaporator, water treatment

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Authors: Subal Kar, Madhuja Ghosh, Amitesh Kumar, Arijit Majumder

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Complementary split-ring resonator (CSRR) loaded microstrip square patch antenna has been optimally designed with the help of high frequency structure simulator (HFSS). The antenna has been fabricated on the basis of the simulation design data and experimentally tested in anechoic chamber to evaluate its gain, bandwidth, efficiency and polarization characteristics. The CSRR loaded microstrip patch antenna has been found to realize significant size miniaturization (to the extent of 24%) compared to the conventional-type microstrip patch antenna both operating at the same frequency (5.2 GHz). The fabricated antenna could realize a maximum gain of 4.17 dB, 10 dB impedance bandwidth of 34 MHz, efficiency 50.73% and with maximum cross-pol of 10.56 dB down at the operating frequency. This practically designed antenna with its miniaturized size is expected to be useful for airborne and space borne applications at microwave frequency.

Keywords: split ring resonator, metamaterial, CSRR loaded patch antenna, microstrip patch antenna, LC resonator

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: I.-A. Ciobotaru, I.-E. Ciobotaru, D.-I. Vaireanu

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Currently, an ascending trend of battery use may be observed, together with an increase of the generated amount of waste. Efforts have been focused on the recycling of batteries; however, extending their lifetime may be a more adequate alternative, and the development of such methods may prove to be more cost efficient as compared to recycling. In this context, this paper presents the analysis of a proposed process for the reconditioning of some lithium-ions batteries. The analysis is performed based on two criteria, the first one referring to the technical aspect of the reconditioning process and the second to the economic aspects. The main technical parameters taken into consideration are the values of capacitance and internal resistance of the lithium-ion batteries. The economic criterion refers to the evaluation of the efficiency of the reconditioning procedure reported to its total cost for the investigated lithium-ion batteries. Based on the cost analysis, one introduced a novel coefficient that correlates the efficiency of the aforementioned process and its corresponding costs. The reconditioning procedure for the lithium-ion batteries proposed in this paper proved to be valid, efficient, and with reasonable costs.

Keywords: cost assessment, lithium-ion battery, reconditioning coefficient, reconditioning procedure

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Authors: Feyza Şahi̇n, Harun Deni̇zli̇, Mustafa Zabun, Hüseyi̇n OnbaşIoğli

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Heat exchangers are devices that are widely used to transfer heat between fluids due to their temperature differences. As a type of heat exchanger, air coolers are heat exchangers that cool the air as it passes through the fins of the heat exchanger by transferring heat to the refrigerant in the coil tubes of the heat exchanger. An assembled fin and tube heat exchanger consists of a coil block and a casing with a fan mounted on it. The term “Fan hood” is used to define the distance between the fan and the coil block. Air coolers play a crucial role in cooling systems, and their heat transfer performance can vary depending on design parameters. These parameters can be related to the air side or the internal fluid side. For airside efficiency, the distance between the fan and the coil block affects the performance by creating dead zones at the corners of the casing and maldistribution of airflow. Therefore, a detailed study of the effect of the fan hood on the evaporator and the optimum fan hood distance is necessary for an efficient air cooler design. This study aims to investigate the value of the fan hood in a fin and tube-type air cooler heat exchanger through computational fluid dynamics (CFD) simulations and experimental investigations. CFD simulations will be used to study the airflow within the fan hood. These simulations will provide valuable insights to optimize the design of the fan hood. In addition, experimental tests will be carried out to validate the CFD results and to measure the performance of the fan hood under real conditions. The results will help us to understand the effect of fan hood design on evaporator efficiency and contribute to the development of more efficient cooling systems. This study will provide essential information for evaporator design and improving the energy efficiency of cooling systems.

Keywords: heat exchanger, fan hood, heat exchanger performance, air flow performance

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Authors: Usarat Thawornchaisit, Kamalasiri Juthaisong, Kasama Parsongjeen, Phonsiri Phoengchan

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In this study, sludge samples that were collected from the wastewater treatment plant of a printed circuit board manufacturing industry in Thailand were subjected to acid extraction using sulfuric acid as the chemical extracting agent. The effects of sulfuric acid concentration (A), the ratio of a volume of acid to a quantity of sludge (B) and extraction time (C) on the efficiency of copper extraction were investigated with the aim of finding the optimal conditions for maximum removal of copper from the wastewater treatment sludge. Factorial experimental design was employed to model the copper extraction process. The results were analyzed statistically using analysis of variance to identify the process variables that were significantly affected the copper extraction efficiency. Results showed that all linear terms and an interaction term between volume of acid to quantity of sludge ratio and extraction time (BC), had statistically significant influence on the efficiency of copper extraction under tested conditions in which the most significant effect was ascribed to volume of acid to quantity of sludge ratio (B), followed by sulfuric acid concentration (A), extraction time (C) and interaction term of BC, respectively. The remaining two-way interaction terms, (AB, AC) and the three-way interaction term (ABC) is not statistically significant at the significance level of 0.05. The model equation was derived for the copper extraction process and the optimization of the process was performed using a multiple response method called desirability (D) function to optimize the extraction parameters by targeting maximum removal. The optimum extraction conditions of 99% of copper were found to be sulfuric acid concentration: 0.9 M, ratio of the volume of acid (mL) to the quantity of sludge (g) at 100:1 with an extraction time of 80 min. Experiments under the optimized conditions have been carried out to validate the accuracy of the Model.

Keywords: acid treatment, chemical extraction, sludge, waste management

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Authors: Kalyani Mer

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Hydrogen peroxide (H₂O₂) is one of the most efficient and commonly used oxidants in in-situ chemical oxidation (ISCO) of organic contaminants. In the present study, we investigated the activation of H₂O₂ by heavy metal (nickel and lead metal ions) loaded biochar for phenol degradation in an aqueous solution (concentration = 100 mg/L). It was found that H₂O₂ can be effectively activated by biochar, which produces hydroxyl (•OH) radicals owing to an increase in the formation of persistent free radicals (PFRs) on biochar surface. Ultrasound treated (30s duration) biochar, chemically activated by 30% phosphoric acid and functionalized by diethanolamine (DEA) was used for the adsorption of heavy metal ions from aqueous solutions. It was found that modified biochar could remove almost 60% of nickel in eight hours; however, for lead, the removal efficiency reached up to 95% for the same time duration. The heavy metal loaded biochar was further used for the degradation of phenol in the absence and presence of H₂O₂ (20 mM), within 4 hours of reaction time. The removal efficiency values for phenol in the presence of H₂O₂ were 80.3% and 61.9%, respectively, by modified biochar loaded with nickel and lead metal ions. These results suggested that the biochar loaded with nickel exhibits a better removal capacity towards phenol than the lead loaded biochar when used in H₂O₂ based oxidation systems. Meanwhile, control experiments were set in the absence of any activating biochar, and the removal efficiency was found to be 19.1% when only H₂O₂ was added in the reaction solution. Overall, the proposed approach serves a dual purpose of using biochar for heavy metal ion removal and treatment of organic contaminants by further using the metal loaded biochar for H₂O₂ activation in ISCO processes.

Keywords: biochar, ultrasound, heavy metals, in-situ chemical oxidation, chemical activation

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Authors: Tayirjan Taylor Isimjan, Essam Jamea, Muien Qaryouti

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The demand for efficient greenhouse production is escalating, necessitating continuous improvements in controlled plant growth environments. Central to maximizing growth are critical light-related factors, including quantity, quality, and geometric distribution of intercepted radiation. This becomes particularly crucial in regions like the Middle East, characterized by high solar radiation and dusty atmospheric conditions. Existing greenhouse technologies often rely on additional expensive equipment to manage light conditions effectively. In this study, we propose a distinct approach employing functional coatings to mitigate dust and block UV and IR radiation, thereby conserving energy and enhancing productivity. By combining UV-IR reflective coatings with dust mitigation strategies, we aim to address both environmental challenges and energy consumption issues faced by greenhouse agriculture in Saudi Arabia.

Keywords: greenhouse, UV-IR reflective coatings, dust mitigation, energy efficiency, productivity

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Authors: Sonali Mohite

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Severe changes to Organizational Sustainability (OS) have been brought about by the COVID-19 pandemic. This situation forces organizations to tackle the competencies required to augment Employee Resilience (ER) and make profitable growth. This study explores how employee resilience contributes to both individual and organizational success in the wake of the COVID-19 pandemic. We suggest that employees who possess strong coping mechanisms and adaptability are better equipped to handle ongoing disruptions, resulting in improved individual performance metrics like productivity, engagement, and innovative thinking. Hence, exploring the efficiency of ER in improving EP and OS in Post-Pandemic (PP) is the aim of this research. By utilizing convenience sampling techniques, a total of 422 employees have been collected from numerous organizations. After that, the study’s hypothesis is analysed by using Structural Equation Modelling (SEM). As per the study’s findings, the ER factors of “Job Satisfaction (JS)”, “Self-Efficacy (SE)”, “Supervisors’ Support (SS)”, and “Facilitating Conditions (FC)” have positive and significant associations with organizational efficiency. Furthermore, the study’s findings also exhibited that there is the most important relation between SE and EOP.

Keywords: employee resilience, employee performance, organizational performance, sustainability, post-pandemic

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Authors: Daehyoung Kim, Pervez Khan, Hoon Kim

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Efficient utilization of spectrum resources is a fundamental issue of wireless communications due to its scarcity. To improve the efficiency of spectrum utilization, the spectrum sharing for unlicensed bands is being regarded as one of key technologies in the next generation wireless networks. A number of schemes such as Listen-Before-Talk(LBT) and carrier sensor adaptive transmission (CSAT) have been suggested from this aspect, but more efficient sharing schemes are required for improving spectrum utilization efficiency. This work considers an opportunistic transmission approach and a dynamic Contention Window (CW) adjustment scheme for LTE-U users sharing the unlicensed spectrum with Wi-Fi, in order to enhance the overall system throughput. The decision criteria for the dynamic adjustment of CW are based on the collision evaluation, derived from the collision probability of the system. The overall performance can be improved due to the adaptive adjustment of the CW. Simulation results show that our proposed scheme outperforms the Distributed Coordination Function (DCF) mechanism of IEEE 802.11 MAC.

Keywords: spectrum sharing, adaptive opportunistic transmission, unlicensed bands, heterogeneous networks

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Authors: M. P. Tripathi, Priti Tiwari

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Soil and Water Assessment Tool (SWAT) is a distributed parameter continuous time model and was tested on daily and fortnightly basis for a small agricultural watershed (Dhangaon) of Chhattisgarh state in India. The SWAT model recently interfaced with ArcGIS and called as ArcSWAT. The watershed and sub-watershed boundaries, drainage networks, slope and texture maps were generated in the environment of ArcGIS of ArcSWAT. Supervised classification method was used for land use/cover classification from satellite imageries of the years 2009 and 2012. Manning's roughness coefficient 'n' for overland flow and channel flow and Fraction of Field Capacity (FFC) were calibrated for monsoon season of the years 2009 and 2010. The model was validated on a daily basis for the years 2011 and 2012 by using the observed daily rainfall and temperature data. Calibration and validation results revealed that the model was predicting the daily surface runoff and sediment yield satisfactorily. Sensitivity analysis showed that the annual sediment yield was inversely proportional to the overland and channel 'n' values whereas; annual runoff and sediment yields were directly proportional to the FFC. The model was also tested (calibrated and validated) for the fortnightly runoff and sediment yield for the year 2009-10 and 2011-12, respectively. Simulated values of fortnightly runoff and sediment yield for the calibration and validation years compared well with their observed counterparts. The calibration and validation results revealed that the ArcSWAT model could be used for identification of critical sub-watershed and for developing management scenarios for the Dhangaon watershed. Further, the model should be tested for simulating the surface runoff and sediment yield using generated rainfall and temperature before applying it for developing the management scenario for the critical or priority sub-watersheds.

Keywords: watershed, hydrologic and water quality, ArcSWAT model, remote sensing, GIS, runoff and sediment yield

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Authors: Shehret Tilvaldyev, Jorge Flores-Garay, Alfredo Villanueva, Erwin Martinez, Lazaro Rico

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The efficiency of modern transportation is severely compromised by the prevalence of turbulent drag. The high level of turbulent skin-friction occurring, e.g., on the surface of an aircraft, automobiles or the carriage of a high-speed train, is responsible for excess fuel consumption and increased carbon emissions. The environmental, political, and economic pressure to improve fuel efficiency and reduce carbon emissions associated with transportation means that reducing turbulent skin-friction drag is a pressing engineering problem. The dynamic pressure of subsonic airflow around solid objects creates lift, but also induces drag force. This paper is presenting the results of laboratory experiments, investigating appearance and magnitude of dynamic pressure in micro scale of subsonic air flow around right cylinder and symmetrical airfoil.

Keywords: airflow, dynamic pressure, micro scale, symmetric object

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Authors: Nataša Todorović, Jovana Nikolov, Ivana Stojković, Milan Vraneš, Jovana Panić, Slobodan Gadžurić

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The detection of ²¹⁰Pb levels in aquatic environments evokes interest in various scientific studies. Its precise determination is important not only for the radiological assessment of drinking waters but also ²¹⁰Pb, and ²¹⁰Po distribution in the marine environment are significant for the assessment of the removal rates of particles from the ocean and particle fluxes during transport along the coast, as well as particulate organic carbon export in the upper ocean. Measurement techniques for ²¹⁰Pb determination, gamma spectrometry, alpha spectrometry, or liquid scintillation counting (LSC) are either time-consuming or demand expensive equipment or complicated chemical pre-treatments. However, one other possibility is to measure ²¹⁰Pb on an LS counter if it is in equilibrium with its progeny ²¹⁰Bi - through the Cherenkov counting method. It is unaffected by the chemical quenching and assumes easy sample preparation but has the drawback of lower counting efficiencies than standard LSC methods, typically from 10% up to 20%. The aim of the presented research in this paper is to investigate the possible increment of detection efficiency of Cherenkov counting during ²¹⁰Pb/²¹⁰Bi detection on an LS counter Quantulus 1220. Considering naturally low levels of ²¹⁰Pb in aqueous samples, the addition of ionic liquids to the counting vials with the analysed samples has the benefit of detection limit’s decrement during ²¹⁰Pb quantification. Our results demonstrated that ionic liquid, 1-butyl-3-methylimidazolium salicylate, is more efficient in Cherenkov counting efficiency increment than the previously explored 2-hydroxypropan-1-amminium salicylate. Consequently, the impact of a few other ionic liquids that were synthesized with the same cation group (1-butyl-3-methylimidazolium benzoate, 1-butyl-3-methylimidazolium 3-hydroxybenzoate, and 1-butyl-3-methylimidazolium 4-hydroxybenzoate) was explored in order to test their potential influence on Cherenkov counting efficiency. It was confirmed that, among the explored ones, only ionic liquids in the form of salicylates exhibit a wavelength shifting effect. Namely, the addition of small amounts (around 0.8 g) of 1-butyl-3-methylimidazolium salicylate increases the detection efficiency from 16% to >70%, consequently reducing the detection threshold by more than four times. Moreover, the addition of ionic liquids could find application in the quantification of other radionuclides besides ²¹⁰Pb/²¹⁰Bi via Cherenkov counting method.

Keywords: liquid scintillation counting, ionic liquids, Cherenkov counting, ²¹⁰PB/²¹⁰BI in water

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Authors: Shahram Nowrouzieh, Abbas Rezaei Asl, Mohamad Ali Jafari

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Cotton, as a strategic crop, plays an important role in providing human food and clothing need, because of its oil, protein, and fiber. Iran has been one of the largest cotton producers in the world in the past, but unfortunately, for economic reasons, its production is reduced now. One of the ways to reduce the cost of cotton production is to expand the mechanization of cotton harvesting. Iranian farmers do not accept the function of cotton harvesters. One reason for this lack of acceptance of cotton harvesting machines is the number of field losses on these machines. So, the majority of cotton fields are harvested by hand. Although the correct setting of the harvesting machine is very important in the cotton losses, the morphological properties of the cotton plant also affect the performance of cotton harvesters. In this study, the effect of some cotton morphological properties such as the height of the cotton plant, number, and length of sympodial and monopodial branches, boll dimensions, boll weight, number of carpels and bracts angle were evaluated on the performance of cotton picker. In this research, the efficiency of John Deere 9920 spindle Cotton picker is investigated on five different Iranian cotton cultivars. The results indicate that there was a significant difference between the five cultivars in terms of machine harvest efficiency. Golestan cultivar showed the best cotton harvester performance with an average of 87.6% of total harvestable seed cotton and Khorshid cultivar had the least cotton harvester performance. The principal component analysis showed that, at 50.76% probability, the cotton picker efficiency is affected by the bracts angle positively and by boll dimensions, the number of carpels and the height of cotton plants negatively. The seed cotton remains (in the plant and on the ground) after harvester in PCA scatter plot were in the same zone with boll dimensions and several carpels.

Keywords: cotton, bract, harvester, carpel

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Authors: Lauren M. Cook, Tove A. Larsen

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Due to their potential to provide numerous ecosystem services, green roofs have been proposed as a solution to mitigate a growing list of environmental challenges, like urban flooding and urban heat island effect. Because of their cooling effect, green roofs placed below rooftop photovoltaic (PV) panels also have the potential to increase PV panel efficiency. Sedums, a type of succulent plant, are commonly used on green roofs because they are drought and heat tolerant. However, other plant species, such as grasses or plants with reflective properties, have been shown to reduce more runoff and cool the rooftop more than succulent species due to high evapotranspiration (ET) and reflectivity, respectively. The goal of this study is to evaluate whether vegetation with high ET or reflectivity can influence multiple co-benefits of the green roof. Four small scale green roofs in Zurich are used as an experiment to evaluate differences in (1) the timing and amount of runoff discharged from the roof, (2) the air temperature above the green roof, and (3) the temperature and efficiency of solar panels placed above the green roof. One grass species, Silene vulgaris, and one silvery species, Stachys byzantia, are compared to a baseline of Sedum album and black roof. Initial results from August to November 2019 show that the grass species has retained more cumulative runoff and led to a lower canopy temperature than the other species. Although the results are not yet statistically significant, they may suggest that plants with higher ET will have a greater effect on canopy temperature than plants with high reflectivity. Future work will confirm this hypothesis and evaluate whether it holds true for solar panel temperature and efficiency.

Keywords: co-benefit estimation, green cities, green roofs, solar panels

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Authors: Kumaran Narayanan, Andrew N. Osahor

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E. coli has been engineered by our group and by others as a vector to deliver DNA into cultured human and animal cells. However, so far conditions to improve gene delivery using this vector have not been investigated, resulting in a major gap in our understanding of the requirements for this vector to function optimally. Our group recently published novel data showing that simple addition of the DNA transfection reagent Lipofectamine increased the efficiency of the E. coli vector by almost 3-fold, providing the first strong evidence that further optimization of bactofection is possible. This presentation will discuss advances that demonstrate the effects of several intracellular strategies that improve the efficiency of this vector. Conditions that promote endosomal escape of internalized bacteria to evade lysosomal destruction after entry in the cell, a known obstacle limiting this vector, are elucidated. Further, treatments that increase bacterial lysis so that the vector can release its transgene into the mammalian environment for expression will be discussed. These experiments will provide valuable new insight to advance this E. coli system as an important class of vector technology for genetic correction of human disease models in cells and whole animals.

Keywords: DNA, E. coli, gene expression, vector

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Gustavo Funes, Eduardo Peters, Jose Delpiano

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It is widely known that photovoltaic technology has been massively distributed over the last decade despite its low-efficiency ratio. Dust deposition reduces this efficiency even more, lowering the energy production and module lifespan. In this work, we developed an artificial vision algorithm based on CIELAB color space to identify dust over panels in an autonomous way. We performed several experiments photographing three different types of panels, 30W, 340W and 410W. Those panels were soiled artificially with uniform and non-uniform distributed dust. The algorithm proposed uses statistical tools to provide a simulation with a 100% soiled panel and then performs a comparison to get the percentage of dirt in the experimental data set. The simulation uses a seed that is obtained by taking a dust sample from the maximum amount of dust from the dataset. The final result is the dirt percentage and the possible distribution of dust over the panel. Dust deposition is a key factor for plant owners to determine cleaning cycles or identify nonuniform depositions that could lead to module failure and hot spots.

Keywords: dust detection, photovoltaic, artificial vision, soiling

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Authors: Tomiwa, Akinyemi Clement

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Tropical regions experience diverse and complex precipitation patterns, posing significant challenges for accurate rainfall estimation and forecasting. This study addresses the problem of effectively classifying tropical rain types and refining the Z-R (Reflectivity-Rain Rate) relationship to enhance rainfall estimation accuracy. Through a combination of remote sensing, meteorological analysis, and machine learning, the research aims to develop an advanced classification framework capable of distinguishing between different types of tropical rain based on their unique characteristics. This involves utilizing high-resolution satellite imagery, radar data, and atmospheric parameters to categorize precipitation events into distinct classes, providing a comprehensive understanding of tropical rain systems. Additionally, the study seeks to improve the Z-R relationship, a crucial aspect of rainfall estimation. One year of rainfall data was analyzed using a Micro Rain Radar (MRR) located at The Federal University of Technology Akure, Nigeria, measuring rainfall parameters from ground level to a height of 4.8 km with a vertical resolution of 0.16 km. Rain rates were classified into low (stratiform) and high (convective) based on various microstructural attributes such as rain rates, liquid water content, Drop Size Distribution (DSD), average fall speed of the drops, and radar reflectivity. By integrating diverse datasets and employing advanced statistical techniques, the study aims to enhance the precision of Z-R models, offering a more reliable means of estimating rainfall rates from radar reflectivity data. This refined Z-R relationship holds significant potential for improving our understanding of tropical rain systems and enhancing forecasting accuracy in regions prone to heavy precipitation.

Keywords: remote sensing, precipitation, drop size distribution, micro rain radar

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Authors: Shumani Ramuhaheli, Christopher C. Enweremadu, Hilary L. Rutto

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In this study, biodiesel from used cooking oil was produced as purified by washing with water (water wash) and amberlite (dry wash). The work presents the results of short term tests on performance characteristics of diesel engine using both biodiesel-fuel samples. In this investigation, the water wash biodiesel and dry wash biodiesel and diesel were compared for performance using a four-cylinder diesel engine. The torque, brake power, specific fuel consumption and brake thermal efficiency were analyzed. The tests showed that in all cases, dry wash biodiesel performed marginally poorer compared to water wash biodiesel. Except for brake thermal efficiency, diesel fuel had better engine performance characteristics compared to the biodiesel-fuel samples. According to these results, dry washing of biodiesel has a marginal effect on engine performance.

Keywords: biodiesel, engine performance, used cooking oil, water wash, dry wash

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Authors: Piyangkun Kukutapan, Siridech Boonsang

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The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: maximum power point tracking, multilayer perceptron netural network, optimal duty cycle, DC generator

Procedia PDF Downloads 323

Authors: Awadh O. Al-Anazi

Abstract:

As part of the organizational needs toward successful maintaining activities, a proper management system need to be put in place, ensuring the effectiveness of maintenance activities. The management system shall clearly describes the process of identifying, prioritizing, planning, scheduling, execution, and providing valuable feedback for all maintenance activities. Completion and accuracy of the system with proper implementation shall provide the organization with a strong platform for effective maintenance activities that are resulted in efficient outcomes toward business success. The purpose of this research was to introduce a practical tool for measuring the maintenance efficiency level within Saudi organizations. A comprehensive study was launched across many maintenance professionals throughout Saudi leading organizations. The study covered five main categories: work process, identification, planning and scheduling, execution, and performance monitoring. Each category was evaluated across many dimensions to determine its current effectiveness through a five-level scale from 'process is not there' to 'mature implementation'. Wide participation was received, responses were analyzed, and the study was concluded by highlighting major gaps and improvement opportunities within Saudi organizations. One effective implementation of the efficiency enhancement efforts was deployed in Saudi Kayan (one of Sabic affiliates). Below details describes the project outcomes: SK overall maintenance wrench time was measured at 20% (on average) from the total daily working time. The assessment indicates the appearance of several organizational gaps, such as a high amount of reactive work, poor coordination and teamwork, Unclear roles and responsibilities, as well as underutilization of resources. Multidiscipline team was assigned to design and implement an appropriate work process that is capable to govern the execution process, improve the maintenance workforce efficiency, and maximize wrench time (targeting > 50%). The enhanced work process was introduced through brainstorming and wide benchmarking, incorporated with a proper change management plan and leadership sponsorship. The project was completed in 2018. Achieved Results: SK WT was improved to 50%, which resulted in 1) reducing the Average Notification completion time. 2) reducing maintenance expenses on OT and manpower support (3.6 MSAR Actual Saving from Budget within 6 months).

Keywords: efficiency, enhancement, maintenance, work force, wrench time

Procedia PDF Downloads 142

Authors: Fernando Seabra, Giulia P. Flores, Karolina C. Gomes

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Trade liberalizations measures, as import tariff cuts, are not a sufficient trigger for trade growth. Given that price margins are narrow, traders and cargo operators tend to opt out of markets where the process of goods clearance is slow and costly. Excess paperwork and slow customs dispatch not only lead to institutional breakdowns and corruption but also to increasing transaction cost and trade constraints. The objective of this paper is, therefore, two-fold: First, to evaluate the relationship between institutional and infrastructural performance indexes and trade growth in container throughput; and, second, to investigate the causes for differences in container demurrage and detention fees in Latin American countries (using other emerging countries as benchmarking). The analysis is focused on manufactured goods, typically transported by containers. Institutional and infrastructure bottlenecks and, therefore, the country logistics efficiency – measured by the Logistics Performance Index (LPI, World Bank-WB) – are compared with other indexes, such as the Doing Business index (WB) and the Corruption Perception Index (Transparency International). The main results based on the comparison between Latin American countries and the others emerging countries point out in that the growth in containers trade is directly related to LPI performance. It has also been found that the main hypothesis is valid as aspects that more specifically identify trade facilitation and corruption are significant drivers of logistics performance. The exam of port efficiency (demurrage and detention fees) has demonstrated that not necessarily higher level of efficiency is related to lower charges; however, reductions in fees have been more significant within non-Latin American emerging countries.

Keywords: corruption, logistics performance index, container throughput, Latin America

Procedia PDF Downloads 246

Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

Procedia PDF Downloads 125

Authors: Talat Ghomashchi, Zahra Akbari, Shirin Malekpour, Marjan Alimirzaee

Abstract:

Mixing the waste water of industries with natural water has caused environmental pollution. So researcher try to obtain methods and optimum conditions for waste water treatment. One of important stage in waste water treatment is dissolved air flotation. DAF is used for the removal of suspended solids and oils from waste water. In this paper, the effect of several parameters on flotation efficiency with Cationic polyacrylamide as flocculant, was examined, namely, (a) concentration of cationic flocculants, (b) pH (c) fast mixing time, (d) fast mixing speed,(e) slow mixing time,(f) retention time and temperature. After design of experiment, in each trial turbidity of waste water was measured by spectrophotometer. Results show that contribution of pH and concentration of flocculant on flotation efficiency are 75% and 9% respectively. Cationic polyacrylamide led to a significant increase in the settling speed and effect of temperature is negligible. In the optimum condition, the outcome of the DAF unit is increased and amount of suspended solid and oil in waste water is decreased effectively.

Keywords: dissolved air flotation, oil industry, waste water, treatment

Procedia PDF Downloads 525

Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

Procedia PDF Downloads 182

Authors: Abdelrahman Abdelazim

Abstract:

Most industries are looking for technologies that are easy to use, efficient and fast to accomplish. To implement these, factories tend to use advanced systems that could alter complicity to simplicity and rudimentary to advancement. Cloud Manufacturing is a new movement that aims to mirror and integrate cloud computing into manufacturing. Amongst cloud manufacturing various advantages are decreasing the human involvements and increasing the dependency on automated machines, which in turns decreases human errors and increases efficiency. A reliable and extraordinary performance processes with minimum errors are highly desired factors of today’s manufacturers. At the glance it seems to be the best alternative, however, the implementation of a cloud system can be very challenging. This work investigates cloud manufacturing in details, it outlines its advantages and disadvantages by converting a local factory in Kuwait to a cloud-ready system. Initially the flow of the factory’s manufacturing process has been analyzed identifying the bottlenecks and illustrating how cloud manufacturing can eliminate them. Following this an automation process has been analyzed and implemented. A comparison between the process before and after the adaptation has been carried out showing the effects on the cost, the output and the efficiency of the process.

Keywords: cloud manufacturing, automation, Kuwait industrial sector, advanced digital manufacturing

Procedia PDF Downloads 768