Search results for: bird species recognition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4783

Search results for: bird species recognition

4003 RoboWeedSupport-Sub Millimeter Weed Image Acquisition in Cereal Crops with Speeds up till 50 Km/H

Authors: Morten Stigaard Laursen, Rasmus Nyholm Jørgensen, Mads Dyrmann, Robert Poulsen

Abstract:

For the past three years, the Danish project, RoboWeedSupport, has sought to bridge the gap between the potential herbicide savings using a decision support system and the required weed inspections. In order to automate the weed inspections it is desired to generate a map of the weed species present within the field, to generate the map images must be captured with samples covering the field. This paper investigates the economical cost of performing this data collection based on a camera system mounted on a all-terain vehicle (ATV) able to drive and collect data at up to 50 km/h while still maintaining a image quality sufficient for identifying newly emerged grass weeds. The economical estimates are based on approximately 100 hectares recorded at three different locations in Denmark. With an average image density of 99 images per hectare the ATV had an capacity of 28 ha per hour, which is estimated to cost 6.6 EUR/ha. Alternatively relying on a boom solution for an existing tracktor it was estimated that a cost of 2.4 EUR/ha is obtainable under equal conditions.

Keywords: weed mapping, integrated weed management, weed recognition, image acquisition

Procedia PDF Downloads 227
4002 Patient-Friendly Hand Gesture Recognition Using AI

Authors: K. Prabhu, K. Dinesh, M. Ranjani, M. Suhitha

Abstract:

During the tough times of covid, those people who were hospitalized found it difficult to always convey what they wanted to or needed to the attendee. Sometimes the attendees might also not be there. In that case, the patients can use simple hand gestures to control electrical appliances (like its set it for a zero watts bulb)and three other gestures for voice note intimation. In this AI-based hand recognition project, NodeMCU is used for the control action of the relay, and it is connected to the firebase for storing the value in the cloud and is interfaced with the python code via raspberry pi. For three hand gestures, a voice clip is added for intimation to the attendee. This is done with the help of Google’s text to speech and the inbuilt audio file option in the raspberry pi 4. All the five gestures will be detected when shown with their hands via the webcam, which is placed for gesture detection. The personal computer is used for displaying the gestures and for running the code in the raspberry pi imager.

Keywords: nodeMCU, AI technology, gesture, patient

Procedia PDF Downloads 158
4001 Genotyping and Phylogeny of Phaeomoniella Genus Associated with Grapevine Trunk Diseases in Algeria

Authors: A. Berraf-Tebbal, Z. Bouznad, , A.J.L. Phillips

Abstract:

Phaeomoniella is a fungus genus in the mitosporic ascomycota which includes Phaeomoniella chlamydospora specie associated with two declining diseases on grapevine (Vitis vinifera) namely Petri disease and esca. Recent studies have shown that several Phaeomoniella species also cause disease on many other woody crops, such as forest trees and woody ornamentals. Two new species, Phaeomoniella zymoides and Phaeomoniella pinifoliorum H.B. Lee, J.Y. Park, R.C. Summerbell et H.S. Jung, were isolated from the needle surface of Pinus densiflora Sieb. et Zucc. in Korea. The identification of species in Phaeomoniella genus can be a difficult task if based solely on morphological and cultural characters. In this respect, the application of molecular methods, particularly PCR-based techniques, may provide an important contribution. MSP-PCR (microsatellite primed-PCR) fingerprinting has proven useful in the molecular typing of fungal strains. The high discriminatory potential of this method is particularly useful when dealing with closely related or cryptic species. In the present study, the application of PCR fingerprinting was performed using the micro satellite primer M13 for the purpose of species identification and strain typing of 84 Phaeomoniella -like isolates collected from grapevines with typical symptoms of dieback. The bands produced by MSP-PCR profiles divided the strains into 3 clusters and 5 singletons with a reproducibility level of 80%. Representative isolates from each group and, when possible, isolates from Eutypa dieback and esca symptoms were selected for sequencing of the ITS region. The ITS sequences for the 16 isolates selected from the MSP-PCR profiles were combined and aligned with sequences of 18 isolates retrieved from GenBank, representing a selection of all known Phaeomoniella species. DNA sequences were compared with those available in GenBank using Neighbor-joining (NJ) and Maximum-parsimony (MP) analyses. The phylogenetic trees of the ITS region revealed that the Phaeomoniella isolates clustered with Phaeomoniella chlamydospora reference sequences with a bootstrap support of 100 %. The complexity of the pathosystems vine-trunk diseases shows clearly the need to identify unambiguously the fungal component in order to allow a better understanding of the etiology of these diseases and justify the establishment of control strategies against these fungal agents.

Keywords: Genotyping, MSP-PCR, ITS, phylogeny, trunk diseases

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4000 Quantitative and Fourier Transform Infrared Analysis of Saponins from Three Kenyan Ruellia Species: Ruellia prostrata, Ruellia lineari-bracteolata and Ruellia bignoniiflora

Authors: Christine O. Wangia, Jennifer A. Orwa, Francis W. Muregi, Patrick G. Kareru, Kipyegon Cheruiyot, Eric Guantai

Abstract:

Ruellia (syn. Dipteracanthus) species are wild perennial creepers belonging to the Acanthaceae family. These species are reported to possess anti-inflammatory, analgesic, antioxidant, gastroprotective, anticancer, and immuno-stimulant properties. Phytochemical screening of both aqueous and methanolic extracts of Ruellia species revealed the presence of saponins. Saponins have been reported to possess anti-inflammatory, antioxidant, immuno-stimulant, antihepatotoxic, antibacterial, anticarcinogenic, and antiulcerogenic activities. The objective of this study was to quantify and analyze the Fourier transform infrared (FTIR) spectra of saponins in crude extracts of three Kenyan Ruellia species namely Ruellia prostrata (RPM), Ruellia lineari-bracteolata (RLB) and Ruellia bignoniiflora (RBK). Sequential organic extraction of the ground whole plant material was done using petroleum ether (PE), chloroform, ethyl acetate (EtOAc), and absolute methanol by cold maceration, while aqueous extraction was by hot maceration. The plant powders and extracts were mixed with spectroscopic grade KBr and compressed into a pellet. The infrared spectra were recorded using a Shimadzu FTIR spectrophotometer of 8000 series in the range of 3500 cm-1 - 500 cm-1. Quantitative determination of the saponins was done using standard procedures. Quantitative analysis of saponins showed that RPM had the highest quantity of crude saponins (2.05% ± 0.03), followed by RLB (1.4% ± 0.15) and RBK (1.25% ± 0.11), respectively. FTIR spectra revealed the spectral peaks characteristic for saponins in RPM, RLB, and RBK plant powders, aqueous and methanol extracts; O-H absorption (3265 - 3393 cm-1), C-H absorption ranging from 2851 to 2924 cm-1, C=C absorbance (1628 - 1655 cm-1), oligosaccharide linkage (C-O-C) absorption due to sapogenins (1036 - 1042 cm-1). The crude saponins from RPM, RLB and RBK showed similar peaks to their respective extracts. The presence of the saponins in extracts of RPM, RLB and RBK may be responsible for some of the biological activities reported in the Ruellia species.1

Keywords: Ruellia bignoniiflora, Ruellia linearibracteolata, Ruellia prostrata, Saponins

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3999 Plant Water Relations and Forage Quality in Leucaena leucocephala (Lam.) de Wit and Acacia saligna (Labill.) as Affected by Salinity Stress

Authors: Maher J. Tadros

Abstract:

This research was conducted to study the effect of different salinity concentrations on the plant water relation and forage quality on two multipurpose forest trees species seedlings Leucaena leucocephala (Lam.) de wit and Acacia saligna (Labill.). Five different salinity concentrations mixture between sodium chloride and calcium chloride (v/v, 1:1) were applied. The control (Distilled Water), 2000, 4000, 6000, and 8000 ppm were used to water the seedlings for 3 months. The research results presented showed a marked variation among the two species in response to salinity. The Leucaena was able to withstand the highest level of salinity compared to Acacia all over the studied parameters except in the relative water content. Although all the morphological characteristics studied for the two species showed a marked decrease under the different salinity concentrations, except the shoot/root ratio that showed a trend of increase. The water stress measure the leaf water potential was more negative with as the relative water content increase under that saline conditions compared to the control. The forage quality represented by the crude protein and nitrogen content were low at 6000 ppm compared to the 8000 ppm in L. Leucocephala that increased compared that level in A. saligna. Also the results showed that growing both Leucaena and Acacia provide a good source of forage when that grow under saline condition which will be of great benefits to the agricultural sector especially in the arid and semiarid areas were these species can provide forage with high quality forage all year around when grown under irrigation with saline. This research recommended such species to be utilized and grown for forages under saline conditions.

Keywords: plant water relations, growth performance, salinity stress, protein content, forage quality, multipurpose trees

Procedia PDF Downloads 386
3998 Optimization of Ultrasonic Assisted Extraction of Antioxidants and Phenolic Compounds from Coleus Using Response Surface Methodology

Authors: Reihaneh Ahmadzadeh Ghavidel

Abstract:

Free radicals such as reactive oxygen species (ROS) have detrimental effects on human health through several mechanisms. On the other hand, antioxidant molecules reduce free radical generation in biologic systems. Synthetic antioxidants, which are used in food industry, have also negative impact on human health. Therefore recognition of natural antioxidants such as anthocyanins can solve these problems simultaneously. Coleus (Solenostemon scutellarioides) with red leaves is a rich source of anthocyanins compounds. In this study we evaluated the effect of time (10, 20 and 30 min) and temperature (40, 50 and 60° C) on optimization of anthocyanin extraction using surface response method. In addition, the study was aimed to determine maximum extraction for anthocyanin from coleus plant using ultrasound method. The results indicated that the optimum conditions for extraction were 39.84 min at 69.25° C. At this point, total compounds were achieved 3.7451 mg 100 ml⁻¹. Furthermore, under optimum conditions, anthocyanin concentration, extraction efficiency, ferric reducing ability, total phenolic compounds and EC50 were registered 3.221931, 6.692765, 223.062, 3355.605 and 2.614045, respectively.

Keywords: anthocyanin, antioxidant, coleus, extraction, sonication

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3997 Induced Breeding of Neolissochilus hexagonolepis Using Pituitary and Synthetic Hormone under the Agro-Climatic Condition of Meghalaya, India

Authors: Lydia Booney Jyrwa, Rabindra Nath Bhuyan

Abstract:

Chocolate Mahseer (Neolissochilus hexagonolepis) is one of the Mahseer species inhabiting the North-eastern region of India and is a native species to the state of Meghalaya since it can adapt and grow well under the agro climatic conditions of the region. The natural population of this fish has been declining over the years from this part of the country. The natural population of this fish has been declining over the years from this part of the country. The fish is considered as one of the endangered species of the Mahseer group, which is having tremendous scope for culture, sports and tourism. But non-availability of quality seed is a hindrance for the culture of this fish. Thus induced breeding of the fish by hormonal administration with pituitary gland and synthetic hormones is the only reliable method to procure the pure seed of the fish. Chocolate Mahseer was successfully bred at the Hatchery Complex, St. Anthony’s College, Shillong, Meghalaya by using pituitary extract and synthetic hormone viz. ovaprim, ovatide and gonopro-FH. The dose standardized is @ 4mg/kg body weight to both male and female as 1st dose and @ 7.9 mg/kg body weight only to female as 2nd dose for pituitary extract and single dose @ 0.8 ml/kg body weight to female and @ 0.3 ml/kg body weight to male of both ovaprim and ovatide, while a single dose @ 0.9 ml/kg body weight to female and @ 0.3 ml/kg body weight to male of gonopro-FH. The doses are standardized after a series of trial and error experiment performed. The fecundity of the fish was 3500 eggs/ kg body weight. The final hatching percentage achieved was 60%. The survival rate of hatchling was 50% up to fry stage. The use of synthetic hormone and positive response of the fish to the hormone will go in long way for production of quality seed of the fish which in turn help in culture of the species as the fish can be a very good candidate species for the culture in the state. This study will also help in the ranching of the fish in the natural habitat leading to conservation of the species. However, the study should be continued further for the large scale production of seeds.

Keywords: chocolate mahseer, induced breeding, pituitary extract, synthetic hormone

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3996 Analysis of Pathogen Populations Occurring in Oilseed Rape Using DNA Sequencing Techniques

Authors: Elizabeth Starzycka-Korbas, Michal Starzycki, Wojciech Rybinski, Mirosława Dabert

Abstract:

For a few years, the populations of pathogenic fungi occurring in winter oilseed rape in Malyszyn were analyzed. Brassica napus L. in Poland and in the world is a source of energy for both the men (oil), and animals, as post-extraction middling, as well as a motor fuel (oil, biofuel) therefore studies of this type are very important. The species composition of pathogenic fungi can be an indicator of seed yield. The occurrence of oilseed rape pathogens during several years were analyzed using the sequencing method DNA ITS. The results were compared in the gene bank using the program NCBI / BLAST. In field conditions before harvest of oilseed rape presence of pathogens infesting B. napus has been assessed. For example, in 2015, 150 samples have been isolated and applied to PDA medium for the identification of belonging species. From all population has been selected mycelium of 83 isolates which were sequenced. Others (67 isolates) were pathogenic fungi of the genus Alternaria which are easily to recognize. The population of pathogenic species on oilseed rape have been identified after analyzing the DNA ITS and include: Leptosphaeria sp. 38 (L. maculans 25, L. biglobosa 13), Alternaria sp. 29, Fusarium sp. 3, Sclerotinia sclerotiorum 7, heterogeneous 6, total of 83 isolates. The genus Alternaria sp. fungi wear the largest share of B. napus pathogens in particular years. Another dangerous species for oilseed rape was Leptosphaeria sp. Populations of pathogens in each year were different. The number of pathogens occurring in the field and their composition is very important for breeders and farmers because of the possible selection of the most resistant genotypes for sowing in the next growing season.

Keywords: B. napus, DNA ITS Sequencing, pathogenic fungi, population

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3995 Unsupervised Classification of DNA Barcodes Species Using Multi-Library Wavelet Networks

Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

Abstract:

DNA Barcode, a short mitochondrial DNA fragment, made up of three subunits; a phosphate group, sugar and nucleic bases (A, T, C, and G). They provide good sources of information needed to classify living species. Such intuition has been confirmed by many experimental results. Species classification with DNA Barcode sequences has been studied by several researchers. The classification problem assigns unknown species to known ones by analyzing their Barcode. This task has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. To make this type of analysis feasible, heuristics, like progressive alignment, have been developed. Another tool for similarity search against a database of sequences is BLAST, which outputs shorter regions of high similarity between a query sequence and matched sequences in the database. However, all these methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. This method permits to avoid the complex problem of form and structure in different classes of organisms. On empirical data and their classification performances are compared with other methods. Our system consists of three phases. The first is called transformation, which is composed of three steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. The second is called approximation, which is empowered by the use of Multi Llibrary Wavelet Neural Networks (MLWNN).The third is called the classification of DNA Barcodes, which is realized by applying the algorithm of hierarchical classification.

Keywords: DNA barcode, electron-ion interaction pseudopotential, Multi Library Wavelet Neural Networks (MLWNN)

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3994 Hand Motion Trajectory Analysis for Dynamic Hand Gestures Used in Indian Sign Language

Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

Abstract:

Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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3993 Influence of Species and Harvesting Height on Chemical Composition, Buffer Nitrogen Solubility and in vitro Ruminal Fermentation of Browse Tree Leaves

Authors: Thabiso M. Sebolai, Victor Mlambo, Solomon Tefera, Othusitse R. Madibela

Abstract:

In some tree species, sustained herbivory can induce changes in biosynthetic pathways resulting in overproduction of anti-nutritional secondary plant compounds. This inductive mechanism, which has not been demonstrated in semi-arid rangelands of South Africa, may result in browse leaves of lower nutritive value. In this study we investigate the interactive effect of browsing pressure and tree species on chemical composition, buffer nitrogen solubility index (NSI), in vitro ruminal dry matter degradability (IVDMD) and in vitro ruminal N degradability (IVND) of leaves. Leaves from Maytenus capitata, Olea africana, Coddia rudis, Carissa macrocarpa, Rhus refracta, Ziziphus mucronata, Boscia oliedes, Grewia robusta, Phyllanthus vessucosus and Ehretia rigida trees growing in a communal grazing area were harvested at two heights: browsable ( < 1.5 m) and non-browsable ( > 1.5 m), representing high and low browsing pressure, respectively. The type of animals utilizing the communal rangeland includes cattle at 1 livestock unit (450kg)/12 to 15 hectors and goats at 1 livestock unit/4 ha. Harvested leaves were dried, milled and analysed for proximate components, soluble phenolics, condensed tannins, minerals and in vitro ruminal fermentation. A significant plant species and harvesting height interaction effect (P < 0.05) was observed for total nitrogen (N) and soluble phenolics concentration. Tree species and harvesting height affected (P < 0.05) condensed tannin (CTs) content where samples harvested from the non-browsable height had higher (0.61 AU550 nm/200 mg) levels than those harvested at browsable height (0.55 AU550 nm/200 mg) while their interaction had no effects. Macro and micro-minerals were only influenced (P < 0.05) by browse species but not harvesting height. Species and harvesting height interacted (P < 0.05) to influence IVDMD and IVND of leaves at 12, 24 and 36 hours of incubation. The different browse leaves contained moderate to high protein, moderate level of phenolics and minerals, suggesting that they have the potential to provide supplementary nutrients for ruminants during the dry seasons.

Keywords: browse plants, chemical composition, harvesting heights, phenolics

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3992 Analysis of Nonlinear and Non-Stationary Signal to Extract the Features Using Hilbert Huang Transform

Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

Abstract:

It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

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3991 Installing Beehives in Solar Parks to Enhance Local Biodiversity

Authors: Nuria Rubio, María Campo, Joana Ruiz, Paola Vecino

Abstract:

Renewable energies have been proposed for some years as a solution to the ecological crisis caused by traditional fuels. The installation of solar parks for electricity production is therefore necessary for a transition to cleaner energy. Additionally, spaces occupied by solar parks can be ideal places for biodiversity promotion consisting in controlled areas allowing free transit of numerous animal species in absence of phytosanitary products or other substances commonly used in rural areas. The main objective of this project is increasing local biodiversity. Secondary objectives include the installation of beehives with Apis mellifera iberiensis swarms (native honeybee species), the monitoring and periodic evaluation of the state of health and demographic progression of these swarms and study of biodiversity increase in these areas, mainly due to the presence of Apis mellifera iberiensis. Prior to bee-hives installation, a preliminary study of the area is carried out to quantify floral load, biocenosis and geo-climatological characteristics of the area of study for determining the optimal number of hives for the benefit of the local ecosystem. Once beehives set up, the bee-swarms health status is monitored and evaluated quarterly using monitoring systems. Parameters studies are weight, humidity inside the hive, external and internal temperature, and sound inside the hive. Furthermore, a biodiversity study of the area was conducted by direct observation and quantification of species (S) in the area of bee-foraging (1 km around the beehives). A great diversity of species has been detected in the area of study. Therefore, the population of Apis mellifera iberiensis is not displacing other pollinators in the area, on the contrary, results show that it is contributing to the pollination of the different plant species enhancing wild bees’ biodiversity.

Keywords: biodiversity, honeybee, pollination, solar park

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3990 Differentiating Morphological Patterns of the Common Benthic Anglerfishes from the Indian Waters

Authors: M. P. Rajeeshkumar, K. V. Aneesh Kumar, J. L. Otero-Ferrer, A. Lombarte, M. Hashim, N. Saravanane, V. N.Sanjeevan, V. M. Tuset

Abstract:

The anglerfishes are widely distributed from shallow to deep-water habitats and are highly diverse in morphology, behaviour, and niche occupancy patterns. To understand this interspecific variability and degree of niche overlap, we performed a functional analysis of five species inhabiting Indian waters where diversity of deep-sea anglerfishes is very high. The sensory capacities (otolith shape and eye size) were also studied to improve the understanding of coexistence of species. The analyses of fish body and otolith shape clustered species in two morphotypes related to phylogenetic lineages: i) Malthopsis lutea, Lophiodes lugubri and Halieutea coccinea were characterized by a dorso-ventrally flattened body with high swimming ability and relative small otoliths, and ii) Chaunax spp. were distinguished by their higher body depth, lower swimming efficiency, and relative big otoliths. The sensory organs did not show a pattern linked to depth distribution of species. However, the larger eye size in M. lutea suggested a nocturnal feeding activity, whereas Chaunax spp. had a large mouth and deeper body in response to different ecological niches. Therefore, the present study supports the hypothesis of spatial and temporal segregation of anglerfishes in the Indian waters, which can be explained from a functional approach and understanding from sensory capabilities.

Keywords: functional traits, otoliths, niche overlap, fishes, Indian waters

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3989 Adaptive Response of Plants to Environmental Stress: Natural Oil Seepage; The Living Laboratory in Tramutola, Basilicata Region

Authors: Maria Francesca Scannone, Martina Bochicchio

Abstract:

One of the major environmental problems today is hydrocarbon contamination. The promising sustainable technologies for the treatment of these contaminated sites involves the use of biological organisms. In Agri Valley (Basilicata Region) there is a living laboratory (natural oil seeps) where the selective pressure has enriched the environmental matrices with microorganisms, fungi and plant species able to use the hydrocarbons as a source of metabolic energy, to degrade or tolerate hydrocarbons. Observers visiting this area are fascinated by its unspoiled nature, and the condition of the ecosystem does not appear to has been damaged. The amazing resiliency observed in Tramutola site is of key importance to try to bring green remediation technologies, but no research has been done to identify high-performing native species. The aim of this research was to study how natural processes affect the fate of released oil or how individual species or communities of plants and animals are capable of dealing with the burden of otherwise toxic chemicals. The survey of vegetation was carried out, more than 60 species have been identified and divided into tree, shrub and herb layer. Plant data sheets have been completed only for the species that showed the most appropriate properties for phytoremediation. In general, members of the Salicales, Cyperales, Poales, Fagales, Cornales, Equisetales orders were the most commonly identified orders. They are pioneer plants with high adaptive capacity and vegetative propagation. The literature review has highlighted the existence of rhizosphere effect and a green liver model on selected plants. The study provides significant information on the environmental stress adaptation processes of many indigenous plants that are living and growing on a natural leak of crude oil and gas that migrates up through subsurface.

Keywords: green liver, hydrocarbon degradation, oil seeps, phytoremediation

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3988 Freshwater Fish Diversity and IUCN Status of Glacial-fed (Bheri) and Spring-fed (Babai) Rivers in the Wake of Inter-basin Water Transfer

Authors: Kumar Khatri, Bibhuti Ranjan Jha, Smriti Gurung, Udhab Raj Khadka

Abstract:

Freshwater fishes are crucial components of aquatic ecosystems but are being affected by a range of anthropogenic activities. A large number of freshwater bodies in Nepal are under different anthropogenic threats, thereby affecting freshwater biodiversity, including fish fauna. Inter-basin water transfer (IBWT) involving damming and diversion has been considered as one of the major threats to the rivers, yet many such projects are in the pipeline. Impact assessment of such projects include generation of baseline information on different biotic and abiotic variables. The aim of this study was to generate baseline information on fish diversity from the glacial-fed Bheri and the spring-fed Babai rivers and their selected tributaries from Western Nepal in the wake of the first inter-basin water transfer from the former to the latter. A total of 10 sites, 5 each from Bheri and Babai systems, were chosen strategically. Seasonal electrofishing was conducted in 2018 following the standard method. A total of 32 species with Catch per Unite Effort (CPUE) of 46.94±24.06 from Bheri and 42 species with CPUE of 63.02±51.80 from Babai were recorded. Cyprinidae, followed by Nemacheilidae, were the most dominant fish Family in both river systems. Barilius vagra and Schistura beavani were the most dominant species in the Bheri and the Babai systems, respectively. Species richness and abundance showed a significant difference between the rivers. The difference in fish assemblages reflects differences in the ecological regimes of these rivers. Of the total species, at least 8 are in the threatened categories of the IUCN Red List, which need active conservation measures. The findings provide a reference to assess the impacts of water transfers on fish in these river systems and could be helpful to other similar river systems in the future.

Keywords: babai river, bheri river, fish diversity, damming

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3987 Comparison Study of Machine Learning Classifiers for Speech Emotion Recognition

Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

Abstract:

In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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3986 The Pigeon Circovirus Evolution and Epidemiology under Conditions of One Loft Race Rearing System: The Preliminary Results

Authors: Tomasz Stenzel, Daria Dziewulska, Ewa Łukaszuk, Joy Custer, Simona Kraberger, Arvind Varsani

Abstract:

Viral diseases, especially those leading to impairment of the immune system, are among the most important problems in avian pathology. However, there is not much data available on this subject other than commercial poultry bird species. Recently, increasing attention has been paid to racing pigeons, which have been refined for many years in terms of their ability to return to their place of origin. Currently, these birds are used for races at distances from 100 to 1000 km, and winning pigeons are highly valuable. The rearing system of racing pigeons contradicts the principles of biosecurity, as birds originating from various breeding facilities are commonly transported and reared in “One Loft Race” (OLR) facilities. This favors the spread of multiple infections and provides conditions for the development of novel variants of various pathogens through recombination. One of the most significant viruses occurring in this avian species is the pigeon circovirus (PiCV), which is detected in ca. 70% of pigeons. Circoviruses are characterized by vast genetic diversity which is due to, among other things, the recombination phenomenon. It consists of an exchange of fragments of genetic material among various strains of the virus during the infection of one organism. The rate and intensity of the development of PiCV recombinants have not been determined so far. For this reason, an experiment was performed to investigate the frequency of development of novel PiCV recombinants in racing pigeons kept in OLR-type conditions. 15 racing pigeons originating from 5 different breeding facilities, subclinically infected with various PiCV strains, were housed in one room for eight weeks, which was supposed to mimic the conditions of OLR rearing. Blood and swab samples were collected from birds every seven days to recover complete PiCV genomes that were amplified through Rolling Circle Amplification (RCA), cloned, sequenced, and subjected to bioinformatic analyses aimed at determining the genetic diversity and the dynamics of recombination phenomenon among the viruses. In addition, virus shedding rate/level of viremia, expression of the IFN-γ and interferon-related genes, and anti-PiCV antibodies were determined to enable the complete analysis of the course of infection in the flock. Initial results have shown that 336 full PiCV genomes were obtained, exhibiting nucleotide similarity ranging from 86.6 to 100%, and 8 of those were recombinants originating from viruses of different lofts of origin. The first recombinant appeared after seven days of experiment, but most of the recombinants appeared after 14 and 21 days of joint housing. The level of viremia and virus shedding was the highest in the 2nd week of the experiment and gradually decreased to the end of the experiment, which partially corresponded with Mx 1 gene expression and antibody dynamics. The results have shown that the OLR pigeon-rearing system could play a significant role in spreading infectious agents such as circoviruses and contributing to PiCV evolution through recombination. Therefore, it is worth considering whether a popular gambling game such as pigeon racing is sensible from both animal welfare and epidemiological point of view.

Keywords: pigeon circovirus, recombination, evolution, one loft race

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3985 Nutritional Value and Forage Quality Indicators in Some Rangeland’s Species at Different Vegetation Forms

Authors: Reza Dehghani Bidgoli

Abstract:

Information on different rangeland plants’ nutritive values at various phonological stages is important in rangelands management. This information helps rangeland managers to choose proper grazing times to achieve higher animal performance without detrimental effects on the rangeland vegetations. Effects of various plant parts’ phonological stages and vegetation types on reserve carbohydrates and forage quality indicators were investigated during the 2009 and 2010. Plant samples were collected in a completely randomized block (CRB) design. The species included, grasses (Secale montanum and Festuco ovina), forbs (Lotus corniculatus and Sanguisorba minor), and shrubs (Kochia prosterata and Salsola rigida). Aerial plant parts’ samples were oven-dried at 80oC for 24 hours, then analyzed for soluble carbohydrates, crude protein (CP), acid detergent fiber (ADF), dry matter digestible (DMD), and metabolizable energy (ME). Results showed that plants at the seedling stage had more reserve carbohydrates and from the three vegetation types (grass, forbs, and shrub), forbs contained more soluble carbohydrates compared to the other two (grasses and shrubs). Differences in soluble carbohydrate contents of different species at various phonological stages in 2 years were statistically significant. The forage quality indicators (CP, ADF, DMD, and ME) in different species, in different vegetation types, in the 2 years were statistically significant, except for the CP.

Keywords: grazing, soluble carbohydrate, protein, fiber, metabolizeable energy

Procedia PDF Downloads 276
3984 Curvelet Features with Mouth and Face Edge Ratios for Facial Expression Identification

Authors: S. Kherchaoui, A. Houacine

Abstract:

This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

Procedia PDF Downloads 229
3983 Developed Text-Independent Speaker Verification System

Authors: Mohammed Arif, Abdessalam Kifouche

Abstract:

Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

Procedia PDF Downloads 47
3982 Aquatic and Marshy Flora from Fresh Water Wetlands on Quartz Sands in Pinar Del Río, Cuba

Authors: Vidal Pérez Hernández, Enrique González Pendás

Abstract:

The most of the aquatic and marshy flora in Cuba, is located on quartzitic sands ecosystems and they are represented by a wide variety of freshwater wetlands, which are spread in the whole south and south-western plain of Pinar del Río. The survey carried out in these ecosystems offers an updated inventory of these species, showing up their biological type, habit, distribution, and the threat grade to which are subjected, taking into account categories granted by UICN. A remarkable decrease is evidenced, in the total of these species respect to this area; due to deposit processes and deforestation, which are taken place by the human activity and the climatic change. It is linked to others threats like, limitless use of their water reserves for irrigating groves, the cattle raising and intensive fishing. Added to it, its sand with 99% pure crystal quartz, are used for the mining. The combination of all factors has a negative influence on a flora that stores more than 250 species, most of them herbaceous and hydrophytes. In these particular ecosystems were found a 40% endemism from total flora, and more than 80%, are evaluated inside the most sensitive threat categories, and already some of them have been declared as extinct.

Keywords: aquatic flora, marshy flora, quartzitic sands, wetlands

Procedia PDF Downloads 220
3981 Analysis of Alliin and Allicin Contents in Allium tuncelianum

Authors: M. Ipek, A. Cansev, A. Ipek, Y. Sahan

Abstract:

Allium tuncelianum is a close relative of cultivated garlic (A. sativum L.) and naturally grows only in eastern part of Turkey. This species has mild garlic odor and therefore, it is locally consumed as garlic by collecting from its natural flora. This over collection threatens the species to extinction. Although it has morphological resemblance to cultivated garlic, the nutritional value of the species has not been characterized very well. Alliin and allicin are two predominant organosulfur compounds found in cultivated garlic. Allicin derived from alliin precursor gives garlic characteristic odor and most of the garlic health benefits are attributed to this compound. The aims of this work were to determine alliin and allicin contents of A. tuncelianum and to compare them with those of cultivated garlic, onion (A. cepa L.) and leek (A. porrum L.). Alliin and allicin were extracted from 400 mg lyophilized samples and 10 µl extracts were measured with high-performance liquid chromatography attached with diode array detector. The alliin contents of A. tuncelianum genotypes ranged from 2.5 to 7.0 mg/g and the allicin contents changed from 0.5 to 1.5 mg/g, whereas alliin and allicin contents of garlic genotypes ranged from 20.0 to 30.0 mg/g and 3.0 to 6.0 mg/g, respectively. On the other hand, we did not detect any measurable alliin and allicin in onion or leek tissues. In conclusion, alliin and allicin contents of A. tuncelianum were characterized first time in this study, which are about 20% of alliin and allicin contents of cultivated garlic.

Keywords: allicin, alliin, Allium tuncelianum, garlic

Procedia PDF Downloads 361
3980 Harmful Algal Blooming Micro-Algae in Kenya’s Coastal Waters

Authors: Nancy Awuor Oduor, Nils Moosdorf

Abstract:

Harmful Algal Blooms (HABs) are a threat to coastal water quality, marine biodiversity, and human health. The attention on HABs and associated phycotoxins is still very low in tropical coastal developing countries despite the high dependence of local communities on coastal and marine resources for food and livelihoods and the growing evidence of the global increase in HABs frequency, toxicity, and geographical expansion. Lack of HABs monitoring thus creates a high risk of exposure due to uncertainty. This study assessed the spatial and temporal variability and effects of potential HAB-forming species in Kenya’s coastal waters. The preliminary results from 463 sampled collected over a series of 10 coastal surveys conducted over 267 Km of Kenya’s coastline between August 2021 and July 2022 revealed the presence of 87 potential algal blooming species belonging to 47 genera dominated by species capable of producing toxins, causing physical harm and high biomass at 41, 31 and 21 % respectively. The taxonomic composition was also dominated by dinoflagellates at 47%, followed by diatoms, cyanobacteria, and silicoflagellates at 39, 12, and 2%, respectively. About 92 % of the toxin-producing species were established in the creek waters. However, there were no significant variations established in species richness between the dry and wet seasons. Paralytic Shellfish Poisoning (PSP) toxin-producing dinoflagellates Alexandrium spp., Aphanizomenon spp., Gonyaulax spp., Gymnodinium spp., and Brachydinium capitatum, and Amnesic Shellfish Poisoning (ASP) Toxin producing diatoms Amphora spp., Nitzschia spp. and Pseudo-nitzschia spp. Frequented the area in low cell densities ranging between 5 and 1500 cells/L. However, no domoic acid (DA) and saxitoxins (SXTs) were detected during the July surveys. This does not mean that the toxins are absent in the area, and longer studies are recommended.

Keywords: harmful algal blooms, phycotoxins, saxitoxin, domoic acid, Kenya

Procedia PDF Downloads 54
3979 Moths of Indian Himalayas: Data Digging for Climate Change Monitoring

Authors: Angshuman Raha, Abesh Kumar Sanyal, Uttaran Bandyopadhyay, Kaushik Mallick, Kamalika Bhattacharyya, Subrata Gayen, Gaurab Nandi Das, Mohd. Ali, Kailash Chandra

Abstract:

Indian Himalayan Region (IHR), due to its sheer latitudinal and altitudinal expanse, acts as a mixing ground for different zoogeographic faunal elements. The innumerable unique and distributional restricted rare species of IHR are constantly being threatened with extinction by the ongoing climate change scenario. Many of which might have faced extinction without even being noticed or discovered. Monitoring the community dynamics of a suitable taxon is indispensable to assess the effect of this global perturbation at micro-habitat level. Lepidoptera, particularly moths are suitable for this purpose due to their huge diversity and strict herbivorous nature. The present study aimed to collate scattered historical records of moths from IHR and spatially disseminate the same in Geographic Information System (GIS) domain. The study also intended to identify moth species with significant altitudinal shifts which could be prioritised for monitoring programme to assess the effect of climate change on biodiversity. A robust database on moths recorded from IHR was prepared from voluminous secondary literature and museum collections. Historical sampling points were transformed into richness grids which were spatially overlaid on altitude, annual precipitation and vegetation layers separately to show moth richness patterns along major environmental gradients. Primary samplings were done by setting standard light traps at 11 Protected Areas representing five Indian Himalayan biogeographic provinces. To identify significant altitudinal shifts, past and present altitudinal records of the identified species from primary samplings were compared. A consolidated list of 4107 species belonging to 1726 genera of 62 families of moths was prepared from a total of 10,685 historical records from IHR. Family-wise assemblage revealed Erebidae to be the most speciose family with 913 species under 348 genera, followed by Geometridae with 879 species under 309 genera and Noctuidae with 525 species under 207 genera. Among biogeographic provinces, Central Himalaya represented maximum records with 2248 species, followed by Western and North-western Himalaya with 1799 and 877 species, respectively. Spatial analysis revealed species richness was more or less uniform (up to 150 species record per cell) across IHR. Throughout IHR, the middle elevation zones between 1000-2000m encompassed high species richness. Temperate coniferous forest associated with 1500-2000mm rainfall zone showed maximum species richness. Total 752 species of moths were identified representing 23 families from the present sampling. 13 genera were identified which were restricted to specialized habitats of alpine meadows over 3500m. Five historical localities with high richness of >150 species were selected which could be considered for repeat sampling to assess climate change influence on moth assemblage. Of the 7 species exhibiting significant altitudinal ascend of >2000m, Trachea auriplena, Diphtherocome fasciata (Noctuidae) and Actias winbrechlini (Saturniidae) showed maximum range shift of >2500m, indicating intensive monitoring of these species. Great Himalayan National Park harbours most diverse assemblage of high-altitude restricted species and should be a priority site for habitat conservation. Among the 13 range restricted genera, Arichanna, Opisthograptis, Photoscotosia (Geometridae), Phlogophora, Anaplectoides and Paraxestia (Noctuidae) were dominant and require rigorous monitoring, as they are most susceptible to climatic perturbations.

Keywords: altitudinal shifts, climate change, historical records, Indian Himalayan region, Lepidoptera

Procedia PDF Downloads 166
3978 Water End-Use Classification with Contemporaneous Water-Energy Data and Deep Learning Network

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

Abstract:

‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

Procedia PDF Downloads 301
3977 Fruit Identification System in Sweet Orange Citrus (L.) Osbeck Using Thermal Imaging and Fuzzy

Authors: Ingrid Argote, John Archila, Marcelo Becker

Abstract:

In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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3976 New Bioactive Compounds from Two Chrysanthemum Saharian Species (Asteraceae) Growing in Algeria

Authors: Zahia Kabouche, Ouissem Gherboudj, Naima Boutaghane, Ahmed Kabouche, Laurence Voutquenne-Nazabadioko

Abstract:

Chrysanthemum herbs (Asteraceae) are extensively used as food additives and in folk medicine. Anti-cancer, anti-human immunodeficiency virus type 1 (HIV-1), anti-inflammatory, antinociceptive and antiproliferative activities as well as antioxidant effects have been reported for Chrysanthemum species. We report the isolation and identification of flavonoids and new and known terpenoids from the endemic species, C. macrocarpum and C. deserticolum “guertoufa”, used in Algerian Sahara as tea drinks and in “couscous” and soups “Chorba”. Structures of the isolated compounds were established by 1-D and 2-D homo and hetero-nuclear NMR (1H, 13C, COSY, HSQC, HMBC, and NOESY), mass spectrometry, UV and comparison with literature data. C. deserticolum extracts were tested by four methods to identify the antioxidant activity namely, ABTS•+, DPPH• scavenging, CUPRAC and ferrous-ions chelating activity methods. Anti-inflammatory, antinociceptive, antiproliferative and antioxidant activities of C. macrocarpum extracts and isolated compounds are also reported here.

Keywords: Chrysanthemum macrocarpum, C. deserticolum, flavonoids, terpenoids, antioxidant, anti-inflammatory, anti-proliferative

Procedia PDF Downloads 331
3975 Effect of Depth on the Distribution of Zooplankton in Wushishi Lake Minna, Niger State, Nigeria

Authors: Adamu Zubairu Mohammed, Fransis Oforum Arimoro, Salihu Maikudi Ibrahim, Y. I. Auta, T. I. Arowosegbe, Y. Abdullahi

Abstract:

The present study was conducted to evaluate the effect of depth on the distribution of zooplankton and some physicochemical parameters in Tungan Kawo Lake (Wushishi dam). Water and zooplankton samples were collected from the surface, 3.0 meters deep and 6.0 meters deep, for a period of 24 hours for six months. Standard procedures were adopted for the determination of physicochemical parameters. Results have shown significant differences in the pH, DO, BOD Hardness, Na, and Mg. A total of 1764 zooplankton were recorded, comprising 35 species, with cladocera having 18 species (58%), 14 species of copepoda (41%), 3 species of diptera (1.0%). Results show that more of the zooplankton were recorded in the 3.0 meters-deep region compared to the two other depts and a significant difference was observed in the distribution of Ceriodaphnia dubia, Daphnia laevis, and Leptodiaptomus coloradensis. Though the most abundant zooplankton was recorded in the 3.0 meters deep, Leptodiaptomus coloradesnsis, which was observed in the 6.0 meters deep as the most individual observed, this was followed by Daphnia laevis. Canonical correspondence analysis between physicochemical parameters and the zooplankton indicated a good relationship in the Lake. Ceriodaphnia dubia was found to have a good association with oxygen, sodium, and potassium, while Daphnia laevis and Leptodiaptomus coloradensis are in good relationship with magnesium and phosphorus. It was generally observed that this depth does not have much influence on the distribution of zooplankton in Wushishi Lake.

Keywords: zooplankton, standard procedures, canonical correspondence analysis, Wushishi, canonical, physicochemical parameter

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3974 Neuron Efficiency in Fluid Dynamics and Prediction of Groundwater Reservoirs'' Properties Using Pattern Recognition

Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p1), fractured layer (p2), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable gr (gravitational resistance) can be deduced from the elevation and apparent resistivity pa. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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