Search results for: machine harvested grapes

Authors: Fils Olivier Kamanzi

Abstract:

This research Paper shows that materials CFRP were used to rehabilitate 9 Beams and retrofitting of 9 Beams with size (125x250x2300) mm each for M50 grade of concrete with 20% of Volume of Cement replaced by GGBS as a mineral Admixture. Superplasticizer (ForscoConplast SP430) used to reduce the water-cement ratio and maintaining good workability of fresh concrete (Slump test 57mm). Concrete Mix ratio 1:1.56:2.66 with a water-cement ratio of 0.31(ACI codebooks). A sample of 6cubes sized (150X150X150) mm, 6cylinders sized (150ФX300H) mm and 6Prisms sized (100X100X500) mm were cast, cured, and tested for 7,14&28days by compressive, tensile and flexure test; finally, mix design reaches the compressive strength of 59.84N/mm2. 21 Beams were cast and cured for up to 28 days, 3Beams were tested by a two-point loading machine as Control beams. 9 Beams were distressed in flexure by adopting failure up to final Yielding point under two-point loading conditions by taking 90% off Ultimate load. Three sets, each composed of three distressed beams, were rehabilitated by using CFRP sheets, one, two & three layers, respectively, and after being retested up to failure mode. Another three sets were freshly retrofitted also by using CFRP sheets one, two & three layers, respectively, and being tested by a two-point load method of compression strength testing machine. The aim of this study is to determine the flexural Strength & behaviors of repaired and retrofitted Beams by CFRP sheets for gaining good strength and considering economic aspects. The results show that rehabilitated beams increase its strength 47 %, 78 % & 89 %, respectively, to thickness of CFRP sheets and 41%, 51 %& 68 %, respectively too, for retrofitted Beams. The conclusion is that three layers of CFRP sheets are the best applicable in repairing and retrofitting the bonded beams method.

Keywords: retrofitting, rehabilitation, cfrp, rcc beam, flexural strength and behaviors, ggbs, and epoxy resin

Procedia PDF Downloads 85

Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

Abstract:

Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

Procedia PDF Downloads 102

Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

Abstract:

E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

Procedia PDF Downloads 138

Authors: Yuri Bizzoni, Marianne Reboul

Abstract:

Our program compares French and Italian translations of Homer’s Odyssey, from the XVIth to the XXth century. We focus on the third point, showing how distributional semantics systems can be used both to improve alignment between different French translations as well as between the Greek text and a French translation. Although we focus on French examples, the techniques we display are completely language independent.

Keywords: classical receptions, computational linguistics, distributional semantics, Homeric poems, machine translation, translation studies, text alignment

Procedia PDF Downloads 418

Authors: Michele Gattullo, Vito M. Manghisi, Alessandro Evangelista, Enricoandrea Laviola

Abstract:

In this work, we explored the use of Augmented Reality (AR) to support students in laboratory lectures in Distance Learning (DL), designing an application that proved to be ready for use next semester. AR could help students in the understanding of complex concepts as well as increase their motivation in the learning process. However, despite many prototypes in the literature, it is still less used in schools and universities. This is mainly due to the perceived limited advantages to the investment costs, especially regarding changes needed in the teaching modalities. However, with the spread of epidemiological emergency due to SARS-CoV-2, schools and universities were forced to a very rapid redefinition of consolidated processes towards forms of Distance Learning. Despite its many advantages, it suffers from the impossibility to carry out practical activities that are of crucial importance in STEM ("Science, Technology, Engineering e Math") didactics. In this context, AR perceived advantages increased a lot since teachers are more prepared for new teaching modalities, exploiting AR that allows students to carry on practical activities on their own instead of being physically present in laboratories. In this work, we designed an AR application for the support of engineering students in the understanding of assembly drawings of complex machines. Traditionally, this skill is acquired in the first years of the bachelor's degree in industrial engineering, through laboratory activities where the teacher shows the corresponding components (e.g., bearings, screws, shafts) in a real machine and their representation in the assembly drawing. This research aims to explore the effectiveness of AR to allow students to acquire this skill on their own without physically being in the laboratory. In a preliminary phase, we interviewed students to understand the main issues in the learning of this subject. This survey revealed that students had difficulty identifying machine components in an assembly drawing, matching between the 2D representation of a component and its real shape, and understanding the functionality of a component within the machine. We developed a mobile application using Unity3D, aiming to solve the mentioned issues. We designed the application in collaboration with the course professors. Natural feature tracking was used to associate the 2D printed assembly drawing with the corresponding 3D virtual model. The application can be displayed on students’ tablets or smartphones. Users could interact with selecting a component from a part list on the device. Then, 3D representations of components appear on the printed drawing, coupled with 3D virtual labels for their location and identification. Users could also interact with watching a 3D animation to learn how components are assembled. Students evaluated the application through a questionnaire based on the System Usability Scale (SUS). The survey was provided to 15 students selected among those we participated in the preliminary interview. The mean SUS score was 83 (SD 12.9) over a maximum of 100, allowing teachers to use the AR application in their courses. Another important finding is that almost all the students revealed that this application would provide significant power for comprehension on their own.

Keywords: augmented reality, distance learning, STEM didactics, technology in education

Procedia PDF Downloads 113

Authors: Akhila Potluru

Abstract:

Worldwide, more than 250 bodies of water are transboundary, meaning they cross the political boundaries of multiple countries. This creates a system of hydrological, economic, and social interdependence between communities reliant on these water sources. Transboundary water conflicts can occur as a result of this intense interdependence. Many factors contribute to the sparking of transboundary water conflicts, ranging from natural hydrological factors to hydro-political interactions. Previous attempts to predict transboundary water conflicts by analysing changes or trends in the contributing factors have typically failed because patterns in the data are hard to identify. However, there is potential for artificial intelligence and machine learning to fill this gap and identify future ‘hotspots’ up to a year in advance by identifying patterns in data where humans can’t. This research determines the extent to which AI can be used to predict and prevent transboundary water conflicts. This is done via a critical literature review of previous case studies and datasets where AI was deployed to predict water conflict. This research not only delivered a more nuanced understanding of previously undervalued factors that contribute toward transboundary water conflicts (in particular, culture and disinformation) but also by detecting conflict early, governance bodies can engage in processes to de-escalate conflict by providing pre-emptive solutions. Looking forward, this gives rise to significant policy implications and water-sharing agreements, which may be able to prevent water conflicts from developing into wide-scale disasters. Additionally, AI can be used to gain a fuller picture of water-based conflicts in areas where security concerns mean it is not possible to have staff on the ground. Therefore, AI enhances not only the depth of our knowledge about transboundary water conflicts but also the breadth of our knowledge. With demand for water constantly growing, competition between countries over shared water will increasingly lead to water conflict. There has never been a more significant time for us to be able to accurately predict and take precautions to prevent global water conflicts.

Keywords: artificial intelligence, machine learning, transboundary water conflict, water management

Procedia PDF Downloads 88

Authors: M. C. Muya, L. J. Erasmus

Abstract:

Twenty four new born male Holstein calves were divided into two treatments groups and used to evaluate the effects of M. elsdenii NCIMB 41125. The first groups were dosed with 50 ml containing 108 CFU/mL of M. elsdenii NCIMB 41125 (Me) and the control calves were not dosed. Within each of the two treatments groups, calves were divided into three treatment groups (Not dosed: 7 d, 14 d and 21 d vs dosed Me 7 d, Me14 and Me21 d (treatments), each groups contained 4 calves within which two calves were euthanized at 24 h and two calves at 72 h. Calves entered the trial until euthanize at whether 24 or 72 H after dosing time. After receiving colostrum for 3 consecutive days after birth, calves were fed whole milk and had free access to a commercial calf starter pellet and fresh water. Fecal grab samples were taken from each calf in duplicate +24 h or +72 h relative to dosing. Immediately after euthanizing, the digestive tract was harvested, and duplicate rumen and colon digesta samples collected for VFA’s determination and DNA extraction for bacteria count using 16s RNA PCR probe technique. Independent two t-test was performed to compare mean volatile fatty acids. Mixed-effects linear regressions were performed to establish relationships between: 1) M. elsdenii and Me, and between VFA’s and Me using SAS (2009). M. elsdenii NCIMB 41125 was detected in the faeces, colon and rumen of dosed calves at both +24H and +72H and ranged from 1.6 x 106 to 4.9 x 109 cfu/ml, indicating its potential to colonize in the digestive tract of calves. There was a strong positive relationship (R²=0.96; P < 0.0001) between M. elsdenii NCIMB 41125 and M. elsdenii population (cfu/ml) in the rumen, suggesting that the increase in M. elsdenii was due to increased M. elsdenii NCIMB 41125. An increase in butyrate was observed from +24 h to +72 h when calves were dosed on both d 7 and 14. Results showed that Me presented a positive relationship with butyrate (P < 0.001, R² = 0.43) and a concomitant negative relationship with acetate (P = 0.017, R² = -0.33). These results suggest that dosing pre-weaned dairy calves with M. elsdenii NCIMB 41125 has the potential to alter ruminal VFA production through increasing proportions of butyrate at the expense of propionate.

Keywords: calves, megasphaera elsdenii, rumen fermentation, bacteria

Procedia PDF Downloads 376

Authors: Cristian Moisa, Andreea Lupitu, Adriana Csakvari, Dana G. Radu, Leonard Marian Olariu, Georgeta Pop, Dorina Chambre, Lucian Copolovici, Dana Copolovici

Abstract:

Green synthesis of nanoparticles (NPs) represents a promising, accessible, eco-friendly, and safe process with significant applications in biotechnology, pharmaceutical sciences, and farming. The aim of our study was to obtain silver nanoparticles, using plant wastes extracts resulted in the essential oils extraction process: Thymus vulgaris L., Origanum vulgare L., Lavandula angustifolia L., and in hemp processing for seed and fibre, Cannabis sativa. Firstly, we obtained aqueous extracts of thyme, oregano, lavender, and hemp (two monoicous and one dioicous varieties), all harvested in western part of Romania. Then, we determined the chemical composition of the extracts by liquid-chromatography coupled with diode array and mass spectrometer detectors. The compounds identified in the extracts were in agreement with earlier published data, and the determination of the antioxidant activity of the obtained extracts by DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) assays confirmed their antioxidant activity due to their total polyphenolic content evaluated by Folin-Ciocalteu assay. Then, the silver nanoparticles (AgNPs) were successfully biosynthesised, as was demonstrated by UV-VIS, FT-IR spectroscopies, and SEM, by reacting AgNO₃ solution and plant extracts. AgNPs were spherical in shape, with less than 30 nm in diameter, and had a good bactericidal activity against Gram-positive (Staphylococcus aureus) and Gram-negative bacteria (Escherichia coli, Klebsiella pneumoniae, Pseudomonas fluorescens).

Keywords: plant wastes extracts, chemical composition, high performance liquid chromatography mass spectrometer, HPLC-MS, scanning electron microscopy, SEM, silver nanoparticles

Procedia PDF Downloads 166

Authors: Juan Luis Leal, Rafael Maestre, Ovidio López

Abstract:

As innovation progresses, more possibilities are made available to increase the efficiency and reach of solutions for Smart Cities, most of which require the data provided by the Internet of Things (IoT) devices and may even have higher power requirements such as motors or actuators. A reliable power supply with the lowest maintenance is a requirement for the success of these solutions in the long term. Energy harvesting, mainly solar, becomes the solution of choice in most cases, but only if there is enough power to be harvested, which may depend on the device location (e.g., outdoors vs. indoor). This is the case of Smart Waste Containers with compaction systems, which have moderately high-power requirements, and may be installed in places with little sunlight for solar generation. It should be noted that waste is unloaded from the containers with cranes, so sudden and irregular movements may happen, making wired power unviable. In these cases, a wireless power supply may be a great alternative. This paper proposes a cost-effective two coil resonant wireless power transfer (WPT) system and describes its implementation, which has been carried out within an R&D project and validated in real settings with smart containers. Experimental results prove that the developed system achieves wireless power transmission up to 35W in the range of 5 cm to 1 m with a peak efficiency of 78%. The circuit is operated at relatively low resonant frequencies, which combined with enough wire-to-wire separation between the coil windings, reduce the losses caused by the proximity effect and, therefore, allow the use of common stranded wire instead of Litz wire, this without reducing the efficiency significantly. All these design considerations led to a final system that achieves a high efficiency for the desired charging range, simplifying the energy supply for Smart Containers as well as other devices that may benefit from a cost-effective wireless charging system.

Keywords: electromagnetic coupling, resonant wireless charging, smart recycling containers, wireless power transfer

Procedia PDF Downloads 79

Authors: Temenuzhka Spasova, Nadya Yanakieva

Abstract:

Snow modulates the hydrological cycle and influences the functioning of ecosystems and is a significant resource for many populations whose water is harvested from cold regions. Snow observations are important for validating climate models. The accumulation and rapid melt of snow are two of the most dynamical seasonal environmental changes on the Earth’s surface. The actuality of this research is related to the modern tendencies of the remote sensing application in the solution of problems of different nature in the ecological monitoring of the environment. The subject of the study is the dynamic during the different seasons on Livingstone Island, South Shetland Islands in Antarctica and on Svalbard in Arctic. The objects were analyzed and mapped according to the Еuropean Space Agency data (ESA), acquired by sensors Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel 2 MSI and GIS. Results have been obtained for changes in snow coverage during the summer-winter transition and its dynamics in the two hemispheres. The data used is of high time-spatial resolution, which is an advantage when looking at the snow cover. The MSI images are with different spatial resolution at the Earth surface range. The changes of the environmental objects are shown with the SAR images and different processing approaches. The results clearly show that snow and snow melting can be best registered by using SAR data via hh- horizontal polarization. The effect of the researcher on aerospace data and technology enables us to obtain different digital models, structuring and analyzing results excluding the subjective factor. Because of the large extent of terrestrial snow coverage and the difficulties in obtaining ground measurements over cold regions, remote sensing and GIS represent an important tool for studying snow areas and properties from regional to global scales.

Keywords: climate changes, GIS, remote sensing, SAR images, snow coverage

Procedia PDF Downloads 204

Authors: Ayalkibet Mekonnen, Adane Abebe

Abstract:

In hydrological cycle there are many water-related human interventions that modify the natural systems. Rainwater harvesting is one such intervention that involves harnessing of water in the upstream. Water harvesting used in upstream prevents water runoff on downstream mainly disturbance on biodiversity and ecosystems. The main objectives of the study are to assess the effects of water harvesting technologies on downstream water availability in the Woreda. To address the above problem, SWAT model, cost-benefit ratio and optimal control approach was used to analyse the hydrological and socioeconomic impact and tradeoffs on water availability of the community, respectively. The downstream impacts of increasing water consumption in the upstream rain-fed areas of the Bilate and Shala Catchment are simulated using the semi-distributed SWAT model. The two land use scenarios tested at sub basin levels (1) conventional land use represents the current land use practice (Agri-CON) and (2) in-field rainwater harvesting (IRWH), improving soil water availability through rainwater harvesting land use scenario. The simulated water balance results showed that the highest peak mean monthly direct flow obtained from Agri-CON land use (127.1 m3/ha), followed by Agri-IRWH land use (11.5 mm) and LULC 2005 (90.1 m3/ha). The Agri-IRWH scenario reduced direct flow by 10% compared to Agri-CON and more groundwater flow contributed by Agri-IRWH (190 m3/ha) than Agri-CON (125 m3/ha). The overall result suggests that the water yield of the Woreda may not be negatively affected by the Agri-IRWH land use scenario. The technology in the Woreda benefited positively having an average benefit cost ratio of 4.2. Water harvesting for domestic use was not optimal that the value of the water per demand harvested was less than the amount of water needed. Storage tanks, series of check dams, gravel filled dams are an alternative solutions for water harvesting.

Keywords: water harvesting, SWAT model, land use scenario, Agri-CON, Agri-IRWH, trade off, benefit cost ratio

Procedia PDF Downloads 321

Authors: Tarali Kalita, Karabi Dutta

Abstract:

The North Eastern Region of India, with diverse climatic conditions and a wide range of ecological habitats, makes an ideal natural abode for a good number of silk-producing insects. Cocoon is the economically important life stage from where silk of economic importance is obtained. In recent years, silk-based biomaterials have gained considerable attention, which is dependent on the structure and properties of the silkworm cocoons as well as silk yarn. The present investigation deals with the morphological study of cocoons, including cocoon color, cocoon size, shell weight and shell ratio of eleven different species of silk insects collected from different regions of North East India. The Scanning Electron Microscopic study and X-ray photoelectron spectroscopy were performed to know the arrangement of silk threads in cocoons and the atomic elemental analysis, respectively. Further, collected cocoons were degummed and reeled/spun on a reeling machine or spinning wheel to know the filament length, linear density and tensile strength by using Universal Testing Machine. The study showed significant variation in terms of cocoon color, cocoon shape, cocoon weight and filament packaging. XPS analysis revealed the presence of elements (Mass %) C, N, O, Si and Ca in varying amounts. The wild cocoons showed the presence of Calcium oxalate crystals which makes the cocoons hard and needs further treatment to reel. In the present investigation, the highest percentage of strain (%) and toughness (g/den) were observed in Antheraea assamensis, which implies that the muga silk is a more compact packing of molecules. It is expected that this study will be the basis for further biomimetic studies to design and manufacture artificial fiber composites with novel morphologies and associated material properties.

Keywords: cocoon characterization, north-east India, prospects, silk characterization

Procedia PDF Downloads 71

Authors: Xiaoyang Zhao, Kaiying Wang

Abstract:

The choice of stocking density in poultry farming is a potential way for determining welfare level of poultry. However, it is difficult to measure stocking densities in poultry farming because of a lot of variables such as species, age and weight, feeding way, house structure and geographical location in different broiler houses. A method was proposed in this paper to measure the differences of young broilers reared under different stocking densities by sound analysis. Vocalisations of broilers were recorded and analysed under different stocking densities to identify the relationship between sounds and stocking densities. Recordings were made continuously for three-week-old chickens in order to evaluate the variation of sounds emitted by the animals at the beginning. The experimental trial was carried out in an indoor reared broiler farm; the audio recording procedures lasted for 5 days. Broilers were divided into 5 groups, stocking density treatments were 8/m², 10/m², 12/m² (96birds/pen), 14/m² and 16/m², all conditions including ventilation and feed conditions were kept same except from stocking densities in every group. The recordings and analysis of sounds of chickens were made noninvasively. Sound recordings were manually analysed and labelled using sound analysis software: GoldWave Digital Audio Editor. After sound acquisition process, the Mel Frequency Cepstrum Coefficients (MFCC) was extracted from sound data, and the Support Vector Machine (SVM) was used as an early detector and classifier. This preliminary study, conducted in an indoor reared broiler farm shows that this method can be used to classify sounds of chickens under different densities economically (only a cheap microphone and recorder can be used), the classification accuracy is 85.7%. This method can predict the optimum stocking density of broilers with the complement of animal welfare indicators, animal productive indicators and so on.

Keywords: broiler, stocking density, poultry farming, sound monitoring, Mel Frequency Cepstrum Coefficients (MFCC), Support Vector Machine (SVM)

Procedia PDF Downloads 143

Authors: Sahithi Yarlagadda

Abstract:

The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

Procedia PDF Downloads 97

Authors: Andrew C. Eloka Eboka, Freddie L. Inambao

Abstract:

Comparative investigation and assessment of microalgal technology as a biodiesel production option was studied alongside other second generation feedstocks. This was carried out by comparing the fuel properties of species of Chlorella vulgaris, Duneliella spp, Synechococus spp and Senedesmus spp with the feedstock of Jatropha (ex-basirika variety), Hura crepitans, rubber and Natal mahogany seed oils. The micro-algae were cultivated in an open pond using a photobioreactor (New Brunsink set-up model BF-115 Bioflo/CelliGen made in the US) with operating parameters: 14L capacity, working volume of 7.5L media, including 10% inoculum, at optical density of 3.144 @540nm and light intensity of 200 lux, for 23 and 16 days respectively. Various produced/accumulated biomasses were harvested by draining, flocculation, centrifugation, drying and then subjected to lipid extraction processes. The oils extracted from the algae and feedstocks were characterised and used to produce biodiesel fuels, by the transesterification method, using modified optimization protocol. Fuel properties of the final biodiesel products were evaluated for chemo-physical and fuel properties. Results revealed Chlorella vulgaris as the best strain for biomass cultivation, having the highest lipid productivity (5.2mgL-1h-1), the highest rate of CO2 absorption (17.85mgL-1min-1) and the average carbon sequestration in the form of CO2 was 76.6%. The highest biomass productivity was 35.1mgL-1h-1 (Chlorella), while Senedesmus had the least output (3.75mgL-1h-1, 11.73mgL-1min-1). All species had good pH value adaptation, ranging from 6.5 to 8.5. The fuel properties of the micro-algal biodiesel in comparison with Jatropha, rubber, Hura and Natal mahogany were within ASTM specification and AGO used as the control. Fuel cultivation from microalgae is feasible and will revolutionise the biodiesel industry.

Keywords: biodiesel, fuel properties, microalgae, second generation, seed oils, feedstock, photo-bioreactor, open pond

Procedia PDF Downloads 352

Authors: Jaroslav Krutil, František Pochylý, Simona Fialová, Vladimír Habán

Abstract:

A mathematical model of the additional effects of the liquid in the hydrodynamic gap is presented in the paper. An in-compressible viscous fluid is considered. Based on computational modeling are determined the matrices of mass, stiffness and damping. The mathematical model is experimentally verified.

Keywords: computational modeling, mathematical model, hydrodynamic gap, matrices of mass, stiffness and damping

Procedia PDF Downloads 539

Authors: Netanel Stern

Abstract:

Artificial intelligence (AI) algorithms have emerged as powerful tools in the field of psychiatry, offering new possibilities for enhancing diagnosis and treatment outcomes. This article explores the utilization of AI algorithms in psychiatry, highlighting their potential to revolutionize patient care. Various AI algorithms, including machine learning, natural language processing (NLP), reinforcement learning, clustering, and Bayesian networks, are discussed in detail. Moreover, ethical considerations and future directions for research and implementation are addressed.

Keywords: AI, software engineering, psychiatry, neuroimaging

Procedia PDF Downloads 87

Authors: Muhammad Bilal Shaikh

Abstract:

Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 56

Authors: Mohamed Saïd Kahaleras, François Lanzetta, Mohamed Khan, Guillaume Layes, Philippe Nika

Abstract:

This paper presents an experimental work to characterize the dynamic operation of a metal regenerator crossed by dry compressible air alternating flow. Unsteady dynamic measurements concern the pressure, velocity and temperature of the gas at the ends and inside the channels of the regenerator. The regenerators are tested under isothermal conditions and thermal axial temperature gradient.

Keywords: friction factor, oscillating flow, regenerator, stirling machine

Procedia PDF Downloads 489

Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Coarse-grained soils are known and commonly used in a wide range of geotechnical projects, including high earth dams or embankments for their high shear strength. The most important engineering property of these soils is friction angle which represents the interlocking between soil particles and can be applied widely in designing and constructing these earth structures. Friction angle and dilative behavior of coarse-grained soils can be estimated from empirical correlations with in-situ testing and physical properties of the soil or measured directly in the laboratory performing direct shear or triaxial tests. Unfortunately, large-scale testing is difficult, challenging, and expensive and is not possible in most soil mechanic laboratories. So, it is common to remove the large particles and do the tests, which cannot be counted as an exact estimation of the parameters and behavior of the original soil. This paper describes a new methodology to simulate particles grading distribution of a well-graded gravel sample to a smaller scale sample as it can be tested in an ordinary direct shear apparatus to estimate the stress-strain behavior, friction angle, and dilative behavior of the original coarse-grained soil considering its confining pressure, and relative density using a machine learning method. A total number of 72 direct shear tests are performed in 6 different sizes, 3 different confining pressures, and 4 different relative densities. Multivariate Adaptive Regression Spline (MARS) technique was used to develop an equation in order to predict shear strength and dilative behavior based on the size distribution of coarse-grained soil particles. Also, an uncertainty analysis was performed in order to examine the reliability of the proposed equation.

Keywords: MARS, coarse-grained soil, shear strength, uncertainty analysis

Procedia PDF Downloads 150

Authors: Nouf Nasser, Nada Alotaibi, Jazzal Kandiel

Abstract:

This research study is about the use of artificial intelligence in PhotoRoom. When an individual selects a photo, PhotoRoom automagically removes or separates the background from other parts of the photo through the use of artificial intelligence. This will allow an individual to select their desired background and edit it as they wish. The methodology used was an observation, where various reviews and parts of the app were observed. The review section's findings showed that many people actually like the app, and some even rated it five stars. The conclusion was that PhotoRoom is one of the best photo editing apps due to its speed and accuracy in removing backgrounds.

Keywords: removing background, app, artificial intelligence, machine learning

Procedia PDF Downloads 185

Authors: Matthias Steffan, Franz Haas

Abstract:

The production process grinding is one of the latest steps in a value-added manufacturing chain. Within this step, workpiece geometry and surface roughness are determined. Up to this process stage, considerable costs and energy have already been spent on components. According to the current state of the art, therefore, large safety reserves are calculated in order to guarantee a process capability. Especially for non-circular grinding, this fact leads to considerable losses of process efficiency. With present technology, various non-circular geometries on a workpiece must be grinded subsequently in an oscillating process where X- and Q-axis of the machine are coupled. With the approach of RPM-Synchronous Noncircular Grinding, such workpieces can be machined in an ordinary plung grinding process. Therefore, the workpieces and the grinding wheels revolutionary rate are in a fixed ratio. A non-circular grinding wheel is used to transfer its geometry onto the workpiece. The authors use a worldwide unique machine tool that was especially designed for this technology. Highest revolution rates on the workpiece spindle (up to 4500 rpm) are mandatory for the success of this grinding process. This grinding approach is performed in a two-step process. For roughing, a highly porous vitrified bonded grinding wheel with medium grain size is used. It ensures high specific material removal rates for efficiently producing the non-circular geometry on the workpiece. This process step is adapted by a force control algorithm, which uses acquired data from a three-component force sensor located in the dead centre of the tailstock. For finishing, a grinding wheel with a fine grain size is used. Roughing and finishing are performed consecutively among the same clamping of the workpiece with two locally separated grinding spindles. The approach of RPM-Synchronous Noncircular Grinding shows great efficiency enhancement in non-circular grinding. For the first time, three-dimensional non-circular shapes can be grinded that opens up various fields of application. Especially automotive industries show big interest in the emerging trend in finishing machining.

Keywords: efficiency enhancement, finishing machining, non-circular grinding, rpm-synchronous grinding

Procedia PDF Downloads 266

Authors: Mahmoud Mohammad Salem Al-Suod, Ushkarenko O. Alexander, Dorogan I. Olga

Abstract:

New algorithms using microprocessor systems have been proposed for protection the diesel-generator unit in autonomous power systems. The software structure is designed to enhance the control automata of the system, in which every protection module of diesel-generator encapsulates the finite state machine.

Keywords: diesel-generator unit, protection, state diagram, control system, algorithm, software components

Procedia PDF Downloads 398

Authors: Maryna Barushka, Aleh Meshyk

Abstract:

The research analyzes absolute maximum soil temperatures registered at 36 gauge stations in Belarus from 1950 to 2013. The main method applied in the research is cartographic, in particular, trend surface analysis. Warming that had never been so long and intensive before started in 1988. The average temperature in January and February of that year exceeded the norm by 7-7.5 С, in March and April by 3-5С. In general, that year, as well as the year of 2008, happened to be the hottest ones in the whole period of instrumental observation. Yearly average air temperature in Belarus in those years was +8.0-8.2 С, which exceeded the norm by 2.0 – 2.2 С. The warming has been observed so far. The only exception was in 1996 when the yearly average air temperature in Belarus was below normal by 0.5 С. In Belarus the value of trend line of standard temperature deviation in the warmest months (July-August) has been positive for the past 25 years. In 2010 absolute maximum air and soil temperature exceeded the norm at 15 gauge stations in Belarus. The structure of natural processes includes global, regional, and local constituents. Trend surface analysis of the investigated characteristics makes it possible to determine global, regional, and local components. Linear trend surface shows the occurrence of weather deviations on a global scale, outside Belarus. Maximum soil temperature appears to be growing in the south-west direction with the gradient of 5.0 С. It is explained by the latitude factor. Polynomial trend surfaces show regional peculiarities of Belarus. Extreme temperature regime is formed due to some factors. The prevailing one is advection of turbulent flow of the ground layer of the atmosphere. In summer influence of the Azores High producing anticyclones is great. The Gulf Stream current forms the values of temperature trends in a year period. The most intensive flow of the Gulf Stream in the second half of winter and the second half of summer coincides with the periods of maximum temperature trends in Belarus. It is possible to estimate a local component of weather deviations in the analysis of the difference in values of the investigated characteristics and their trend surfaces. Maximum positive deviation (up to +4 С) of averaged soil temperature corresponds to the flat terrain in Pripyat Polesie, Brest Polesie, and Belarusian Poozerie Area. Negative differences correspond to the higher relief which partially compensates extreme heat regime of soils. Another important factor for maximum soil temperature in these areas is peat-bog soils with the least albedo of 8-15%. As yearly maximum soil temperature reaches 40-60 С, this could be both negative and positive factors for Belarus’s environment and economy. High temperature causes droughts resulting in crops dying and soil blowing. On the other hand, vegetation period has lengthened thanks to bigger heat resources, which allows planting such heat-loving crops as melons and grapes with appropriate irrigation. Thus, trend surface analysis allows determining global, regional, and local factors in accumulating heat in the soils of Belarus.

Keywords: soil, temperature, trend surface analysis, warming

Procedia PDF Downloads 120

Authors: Geeta, Richa, M. L. Sharma

Abstract:

Himachal Pradesh, a hilly State of India located in the Western Himalayas, with varied altitudinal gradients and climatic conditions, is a repository of plant diversity and the traditional knowledge associated with plants. The State is inhabited by various tribal communities who usually depend upon local plants for curing various ailments. Utilization of plant resources in their day-to-day life has been an age old practice of the people inhabiting this State. The present study pertains to the tribal district Kinnaur of Himachal Pradesh, located between 77°45’ and 79°00’35” east longitudes and between 31°05’50” and 32°05’15” north altitudes. Being a remote area with only very basic medical facilities, local people mostly use traditional herbal medicines for primary healthcare needs. Traditional healers called “Amji” are usually very secretive in revealing their medicinal knowledge to novice and pass on their knowledge to next generation orally. As a result, no written records of healing herbs are available. The aim of present study was to collect and consolidate the ethno-medicinal knowledge of local people of the district about the use of plants for treating gastrointestinal ailments. The ethnobotanical information was collected from the local practitioners, herbal healers and elderly people having rich knowledge about the medicinal herbs through semi-structured questionnaire and key informant discussions. A total 46 plant species belonging to 40 genera and 24 families have been identified which are used as cure for gastrointestinal ailments. Among the parts used for gastointestinal ailments, aerial parts (14%) were followed by the whole plant (13%), root (8%), leaves (6%), flower (5%), fruit and seed (3%) and tuber (1%). These plant species could be prioritized for conservation and subject to further studies related to phytochemical screening for their authenticity. Most of the medicinal plants of the region are collected from the wild and are often harvested for trade. Sustainable harvesting and domestication of the highly traded species from the study area is needed.

Keywords: Amji, gastrointestinal, Kinnaur, medicinal plants, traditional knowledge

Procedia PDF Downloads 379

Authors: Seong-Jin Cho, Jin Ho Kim

Abstract:

Energy harvesting is the technology which gathers and converts external energies such as light, vibration and heat which are disposed into reusable electrical energy and uses such electrical energy. The vibration energy harvesting is very interesting technology because it produces very high density of energy and unaffected by the climate. Vibration energy can be harvested by the electrostatic, electromagnetic and piezoelectric systems. The electrostatic system has low energy conversion efficiency, and the piezoelectric system is expensive and needs the frequent maintenance because it is made of piezoelectric ceramic. On the other hand, the electromagnetic system has a long life time and high harvesting efficiency, and it is relatively cheap. The electromagnetic harvesting system includes the linear generator and the rotary-type generator. The rotary-type generators require the additional mechanical conversion device if it uses linear motion of vibration. But, the linear generator uses directly linear motion of vibration without a mechanical conversion device, and it has uncomplicated structure and light weight compared with the rotary-type generator. Therefore, the linear electromagnetic generator can be useful in using vibration energy harvesting. The pole transformer systems need electricity sensor system for sending voltage and power information to administrator. Therefore, the battery is essential, and its regular maintenance of replacement is required. In case of the transformer of high location in mountainous areas, the person can’t easily access it resulting in high maintenance cost. To overcome these problems, we designed and developed the linear electromagnetic generator which can replace battery in electricity sensor system for sending voltage and power information of the pole transformer. And, it uses vibration energy of frequency more than 50 Hz by the pole transformer. In order to analyze the electromagnetic characteristics of small linear electric generator, a commercial electromagnetic finite element analysis program "MAXWELL" was used. Then, through the actual production and experiment of linear generator, we confirmed output power of linear generator.

Keywords: energy harvesting, frequency, linear generator, experiment

Procedia PDF Downloads 248

Authors: D. Díaz Fernández, I. Csízi, K. Pető, G. Nagy

Abstract:

An outstanding part of the animal products are based on the grasslands, due to the fact that the grassland ecosystems can be found all over the globe. In places where economical and successful crop production cannot be managed, the grassland based animal husbandry can be an efficient way of food production. In addition, these ecosystems have an important role in carbon sequestration, and with their rich flora – and fauna connected to it – in conservation of biodiversity. The protection of nature, and the sustainable agriculture is getting more and more attention in the European Union, but, looking at the consumers’ needs, the production of healthy food cannot be neglected either. Because of these facts, the effects of two specific composts - which are officially authorized in organic farming, in Agri-environment Schemes and Natura 2000 programs – on grass yields and sward compositions were investigated in a field trial. The investigation took place in Hungary, on a natural grassland based on solonetz soil. Three rates of compost (10 t/ha, 20 t/ha, 30 t/ha) were tested on 3 m X 10 m experimental plots. Every treatment had four replications and both type of compost had four-four control plots too, this way 32 experimental plots were included in the investigations. The yield of the pasture was harvested two-times (in May and in September) and before cutting the plots, measurements on botanical compositions were made. Samples for laboratory analysis were also taken. Dry matter yield of pasture showed positive responses to the rates of composts. The increase in dry matter yield was partly due to some positive changes in sward composition. It means that the proportions of grass species with higher yield potential increased in ground cover of the sward without depressing out valuable native species of diverse natural grasslands. The research results indicate that the use of organic compost can be an efficient way to increase grass yields in a sustainable way.

Keywords: compost application, dry matter yield, native grassland, sward composition

Procedia PDF Downloads 232

Authors: Imane El Karaoui, Mohammed Maaroufi, Hamid Chaikhy

Abstract:

Doubly Fed Induction Generator (DFIG) is one of the most reliable wind generator. Major problem in wind power generation is to generate Sinusoidal signal with very low THD on variable speed caused by inverter two levels used. This paper presents a multi-level inverter whose objective is to reduce the THD and the dimensions of the output filter. This work proposes a three-level NPC-type inverter, the results simulation are presented demonstrating the efficiency of the proposed inverter.

Keywords: DFIG, multilevel inverter, NPC inverter, THD, induction machine

Procedia PDF Downloads 234

Authors: N. Lakshmipathy, Ch. S. N. Murthy, M. Aruna

Abstract:

The design of lighting systems for surface mines is not an easy task because of the unique environment and work procedures encountered in the mines. The primary objective of this paper is to identify the major problems encountered in mine lighting application and to provide guidance in the solution of these problems. In the surface mining reflectance of surrounding surfaces is one of the important factors, which improve the vision, in the night hours. But due to typical working nature in the mines it is very difficult to fulfill these requirements, and also the orientation of the light at work site is a challenging task. Due to this reason machine operator and other workers in a mine need to be able to orient themselves in a difficult visual environment. The haul roads always keep on changing to tune with the mining activity. Other critical area such as dumpyards, stackyards etc. also change their phase with time, and it is difficult to illuminate such areas. Mining is a hazardous occupation, with workers exposed to adverse conditions; apart from the need for hard physical labor, there is exposure to stress and environmental pollutants like dust, noise, heat, vibration, poor illumination, radiation, etc. Visibility is restricted when operating load haul dumper and Heavy Earth Moving Machinery (HEMM) vehicles resulting in a number of serious accidents. one of the leading causes of these accidents is the inability of the equipment operator to see clearly people, objects or hazards around the machine. Results indicate blind spots are caused primarily by posts, the back of the operator's cab, and by lights and light brackets. The careful designed and implemented, lighting systems provide mine workers improved visibility and contribute to improved safety, productivity and morale. Properly designed lighting systems can improve visibility and safety during working in the opencast mines.

Keywords: contrast, efficacy, illuminance, illumination, light, luminaire, luminance, reflectance, visibility

Procedia PDF Downloads 345

Authors: Christina Drosou, Konstantina E. Kyriakopoulou, Andreas Bimpilas, Dimitrios Tsimogiannis, Magdalini C. Krokida

Abstract:

Rationale: Agiorgitiko is one of the most widely-grown and commercially well-established red wine varieties in Greece. Each year viticulture industry produces a large amount of waste consisting of grape skins and seeds (pomace) during a short period. Grapes contain polyphenolic compounds which are partially transferred to wine during winemaking. Therefore, winery wastes could be an alternative cheap source for obtaining such compounds with important antioxidant activity. Specifically, red grape waste contains anthocyanins and flavonols which are characterized by multiple biological activities, including cardioprotective, anti-inflammatory, anti-carcinogenic, antiviral and antibacterial properties attributed mainly to their antioxidant activity. Ultrasound assisted extraction (UAE) is considered an effective way to recover phenolic compounds, since it combines the advantage of mechanical effect with low temperature. Moreover, green solvents can be used in order to recover extracts intended for used in the food and nutraceutical industry. Apart from the extraction, pre-treatment process like drying can play an important role on the preservation of the grape pomace and the enhancement of its antioxidant capacity. Objective: The aim of this study is to recover natural extracts from winery waste with high antioxidant capacity using green solvents so they can be exploited and utilized as enhancers in food or nutraceuticals. Methods: Agiorgitiko grape pomace was dehydrated by air drying (AD) and accelerated solar drying (ASD) in order to explore the effect of the pre-treatment on the recovery of bioactive compounds. UAE was applied in untreated and dried samples using water and water: ethanol (1:1) as solvents. The total antioxidant potential and phenolic content of the extracts was determined using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and Folin-Ciocalteu method, respectively. Finally, the profile of anthocyanins and flavonols was specified using HPLC-DAD analysis. The efficiency of processes was determined in terms of extraction yield, antioxidant activity, phenolic content and the anthocyanins and flavovols profile. Results & Discussion: The experiments indicated that the pre-treatment was essential for the recovery of highly nutritious compounds from the pomace as long as the extracts samples showed higher phenolic content and antioxidant capacity. Water: ethanol (1:1) was considered a more effective solvent on the recovery of phenolic compounds. Moreover, ASD grape pomace extracted with the solvent system exhibited the highest antioxidant activity (IC50=0.36±0.01mg/mL) and phenolic content (TPC=172.68±0.01mgGAE/g dry extract), followed by AD and untreated pomace. The major compounds recovered were malvidin3-O-glucoside and quercetin3-O-glucoside according to the HPLC analysis. Conclusions: Winery waste can be exploited for the recovery of nutritious compounds using green solvents such as water or ethanol. The pretreatment of the pomace can significantly affect the concentration of phenolic compounds, while UAE is considered a highly effective extraction process.

Keywords: agiorgitico grape pomace, antioxidants, phenolic compounds, ultrasound assisted extraction

Procedia PDF Downloads 380