Search results for: machine harvested grapes

Authors: Nawab Yousuf Ali, S. Golam, A. Ameer, Ashok Toru Roy

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This paper develops new morphological rules suitable for Bangla repetition words to be incorporated into an inter lingua representation called Universal Networking Language (UNL). The proposed rules are to be used to combine verb roots and their inflexions to produce words which are then combined with other similar types of words to generate repetition words. This paper outlines the format of morphological rules for different types of repetition words that come from verb roots based on the framework of UNL provided by the UNL centre of the Universal Networking Digital Language (UNDL) foundation.

Keywords: Universal Networking Language (UNL), universal word (UW), head word (HW), Bangla-UNL Dictionary, morphological rule, enconverter (EnCo)

Procedia PDF Downloads 294

Authors: Dmitry Fedoseyev

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The ultimate success of unmanned aerial vehicles (UAVs) depends largely on the effective control of their flight, especially in variable wind conditions. This paper investigates different approaches to selecting the optimal flight level to maximize the range of UAVs. We propose to consider methods based on mathematical models of atmospheric conditions, as well as the use of sensor data and machine learning algorithms to automatically optimize the flight level in real-time. The proposed approaches promise to improve the efficiency and range of UAVs in various wind conditions, which may have significant implications for the application of these systems in various fields, including geodesy, environmental surveillance, and search and rescue operations.

Keywords: drone, UAV, flight trajectory, wind-searching, efficiency

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Authors: Ahmad Abdul-Razzak Aboudi Al-Issa

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Thermal and Hydrodynamic are basic aspects in any hydraulic system and therefore, they must be assessed with regard to this aspect before constructing the system. This assessment needs a good expertise in this aspect to obtain an efficient hydraulic system. Therefore, this study aims to build an expert system called Hydraulic System Calculations (HSC) to ensure a smooth operation for the hydraulic system. The expert system (HSC) had been designed and coded in an user-friendly interactive program called Microsoft Visual Basic 2010. The suggested code provides the designer with a number of choices to resolve the problem of hydraulic oil overheating which may arise during the continuous operation of the hydraulic unit. As a result, the HSC can minimize the human errors, effort, time and cost of hydraulic machine design.

Keywords: fluid power, hydraulic system, thermal and hydrodynamic, expert system

Procedia PDF Downloads 424

Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

Procedia PDF Downloads 426

Authors: Stephen Osakue Amiandamhen, Schwaller Andreas, Martina Meincken, Luvuyo Tyhoda

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Invasive alien tree species are currently being cleared in South Africa as a result of the forest and water imbalances. These species grow wildly constituting about 40% of total forest area. They compete with the ecosystem for natural resources and are considered as ecosystem engineers by rapidly changing disturbance regimes. As such, they are harvested for commercial uses but much of it is wasted because of their form and structure. The waste is being sold to local communities as fuel wood. These species can be considered as potential feedstock for the production of phosphate bonded composites. The presence of bark in wood-based composites leads to undesirable properties, and debarking as an option can be cost implicative. This study investigates the potentials of these invasive species processed without debarking on some fundamental properties of wood-based panels. Some invasive alien tree species were collected from EC Biomass, Port Elizabeth, South Africa. They include Acacia mearnsii (Black wattle), A. longifolia (Long-leaved wattle), A. cyclops (Red-eyed wattle), A. saligna (Golden-wreath wattle) and Eucalyptus globulus (Blue gum). The logs were chipped as received. The chips were hammer-milled and screened through a 1 mm sieve. The wood particles were conditioned and the quantity of bark in the wood was determined. The binding matrix was prepared using a reactive magnesia, phosphoric acid and class S fly ash. The materials were mixed and poured into a metallic mould. The composite within the mould was compressed at room temperature at a pressure of 200 KPa. After initial setting which took about 5 minutes, the composite board was demoulded and air-cured for 72 h. The cured product was thereafter conditioned at 20°C and 70% relative humidity for 48 h. Test of physical and strength properties were conducted on the composite boards. The effect of binder formulation and fly ash content on the properties of the boards was studied using fitted response surface technology, according to a central composite experimental design (CCD) at a fixed wood loading of 75% (w/w) of total inorganic contents. The results showed that phosphate/magnesia ratio of 3:1 and fly ash content of 10% was required to obtain a product of good properties and sufficient strength for intended applications. The proposed products can be used for ceilings, partitioning and insulating wall panels.

Keywords: invasive alien tree species, phosphate bonded composites, physical properties, strength

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Authors: Rohit Mittal, Bright Keswani, Amit Mithal

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This paper provides a sense about the application of computational intelligence techniques used to develop computer games, especially car racing. For the deep sense and knowledge of artificial intelligence, this paper is divided into various sections that is optimization, imitation, innovation and combining approach of optimization and imitation. This paper is mainly concerned with combining approach which tells different aspects of using fitness measures and supervised learning techniques used to imitate aspects of behavior. The main achievement of this paper is based on modelling player behaviour and evolving new game content such as racing tracks as single car racing on single track.

Keywords: evolution algorithm, genetic, optimization, imitation, racing, innovation, gaming

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Authors: Tusar Kanti Dash, Ganapati Panda

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The evaluation of speech quality and intelligence is critical to the overall effectiveness of the Speech Enhancement Algorithms. Several intrusive and non-intrusive measures are employed to calculate these parameters. Non-Intrusive Evaluation is most challenging as, very often, the reference clean speech data is not available. In this paper, a novel non-intrusive speech evaluation measure is proposed using audio features derived from the Stockwell transform. These features are used with the Light Gradient Boosting Machine for the effective prediction of speech quality and intelligibility. The proposed model is analyzed using noisy and reverberant speech from four databases, and the results are compared with the standard Intrusive Evaluation Measures. It is observed from the comparative analysis that the proposed model is performing better than the standard Non-Intrusive models.

Keywords: non-Intrusive speech evaluation, S-transform, light GBM, speech quality, and intelligibility

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: G. Hemath Kumar, H. Mohit, K. Karthick

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One of the most important issues in the composite technology is the repairing of parts of aircraft structures which is manufactured from composite materials. In such applications and also for joining various composite parts together, they are fastened together either using adhesives or mechanical fasteners. The tensile strength of these joints was carried out using Universal Testing Machine (UTM). A parametric study was also conducted to compare the performance of the hybrid joint with varying adherent thickness, adhesive thickness and overlap length. The composition of the material is combination of epoxy resin and carbon fibre under the method of reinforcement. To utilize the full potential of composite materials as structural elements, the strength and stress distribution of these joints must be understood. The study of tensile strength in the members involved under various design conditions and various joints were took place.

Keywords: carbon fiber, FRP composite, MMC, automotive

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Authors: Nabilah Ibrahim, Hafiz Mohd Zaini, Wan Fatin Liyana Mutalib

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Ultrasound equipment or machine is capable to scan in two dimensional (2D) areas. However there are some limitations occur during scanning an object. The problem will occur when scanning process that involving the asymmetric object. In this project, the ultrasound probe holder for asymmetric reflector scanning in 3D image is proposed to make easier for scanning the phantom or object that has asymmetric shape. Initially, the constructed asymmetric phantom that construct will be used in 2D scanning. Next, the asymmetric phantom will be interfaced by the movement of ultrasound probe holder using the Arduino software. After that, the performance of the ultrasound probe holder will be evaluated by using the various asymmetric reflector or phantom in constructing a 3D image

Keywords: ultrasound 3D images, axial and lateral resolution, asymmetric reflector, Arduino software

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

Procedia PDF Downloads 192

Authors: Daniia Nigmatullina, Vlada Kugurakova, Maxim Talanov

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We present a methodology and our plans of anthropomorphic social agent visualization. That includes creation of three-dimensional model of the virtual companion's head and its facial expressions. Talking Head is a cross-disciplinary project of developing of the human-machine interface with cognitive functions. During the creation of a realistic humanoid robot or a character, there might be the ‘uncanny valley’ problem. We think about this phenomenon and its possible causes. We are going to overcome the ‘uncanny valley’ by increasing of realism. This article discusses issues that should be considered when creating highly realistic characters (particularly the head), their facial expressions and speech visualization.

Keywords: anthropomorphic social agent, facial animation, uncanny valley, visualization, 3D modeling

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Authors: Ahmed Abbou, Ali Mousmi, Rachid El Akhrif

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This research paper aims to reduce the chattering phenomenon due to control by sliding mode control applied on a wind energy conversion system based on the doubly fed induction generator (DFIG). Our goal is to offset the effect of parametric uncertainties and come as close as possible to the dynamic response solicited by the control law in the ideal case and therefore force the active and reactive power generated by the DFIG to accurately follow the reference values which are provided to it. The simulation results using Matlab / Simulink demonstrate the efficiency and performance of the proposed technique while maintaining the simplicity of control by first order sliding mode.

Keywords: correction of the equivalent command, DFIG, induction machine, sliding mode controller

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Authors: Ahmed A.D. Sarhan, Chong Feng Duan, Mum Wai Yip, M. Sayuti

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Rapid Prototyping (RP) technologies enable physical parts to be produced from various materials without depending on the conventional tooling. Fused Deposition Modeling (FDM) is one of the famous RP processes used at present. Tensile strength and compressive strength resistance will be identified for different sample structures and different layer orientations of ABS rapid prototype solid models. The samples will be fabricated by a FDM rapid prototyping machine in different layer orientations with variations in internal geometrical structure. The 0° orientation where layers were deposited along the length of the samples displayed superior strength and impact resistance over all the other orientations. The anisotropic properties were probably caused by weak interlayer bonding and interlayer porosity.

Keywords: building orientation, compression strength, rapid prototyping, tensile strength

Procedia PDF Downloads 678

Authors: Danish Laidin, Peter Gostomski, Aaron Marshall, Carlo Carere

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Groundwater contamination of nitrate (NO3-) is becoming more prevalent in regions of intensive and extensive agricultural activities. Household nitrate removal involves using ion exchange membranes and reverse osmosis (RO) systems, whereas industrial nitrate removal may use organic carbon substrates (e.g. methanol) for heterotrophic microbial denitrification. However, these approaches both require high capital investment and operating costs. In this study, denitrification was demonstrated using bio-electrochemical systems (BESs) inoculated from sediments and microbial enrichment cultures. The BES reactors were operated continuously as microbial electrolytic cells (MECs) with a poised potential of -0.7V and -1.1V vs Ag/AgCl. Three parallel MECs were inoculated using hydrogen-driven denitrifying enrichments, stream sediments, and biofilm harvested from a denitrifying biotrickling filter, respectively. These reactors were continuously operated for over a year as various operating conditions were investigated to determine the optimal conditions for electroactive denitrification. The mass loading rate of nitrate was varied between 10 – 70 mg NO3-/d, and the maximum observed nitrate removal rate was 22 mg NO3- /(cm2∙d) with a current of 2.1 mA. For volumetric load experiments, the dilution rate of 1 mM NO3- feed was varied between 0.01 – 0.1 hr-1 to achieve a nitrate loading rate similar to the mass loading rate experiments. Under these conditions, the maximum rate of denitrification observed was 15.8 mg NO3- /(cm2∙d) with a current of 1.7mA. Hydrogen (H2) was supplied intermittently to investigate the hydrogenotrophic potential of the denitrifying biofilm electrodes. H2 supplementation at 0.1 mL/min resulted in an increase of nitrate removal from 0.3 mg NO3- /(cm2∙d) to 3.4 mg NO3- /(cm2∙d) in the hydrogenotrophically subcultured reactor but had no impact on the reactors which exhibited direct electron transfer properties. Results from this study depict the denitrification performance of the immobilized biofilm electrodes, either by direct electron transfer or hydrogen-driven denitrification, and the contribution of the planktonic cells present in the growth medium. Other results will include the microbial community analysis via 16s rDNA amplicon sequencing, varying the effect of poising cathodic potential from 0.7V to 1.3V vs Ag/AgCl, investigating the potential of using in-situ electrochemically produced hydrogen for autotrophic denitrification and adjusting the conductivity of the feed solution to mimic groundwater conditions. These findings highlight the overall performance of sediment inoculated MECs in removing nitrate and will be used for the future development of sustainable solutions for the treatment of nitrate polluted groundwater.

Keywords: bio-electrochemical systems, groundwater, electroactive denitrification, microbial electrolytic cell

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Authors: Eric Shannon, Mark J. McGuire, John P. Parmigiani

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A hazard associated with the use of timber harvesters is chain shot. Harvester saw chain is subjected to large dynamic mechanical stresses which can cause it to fracture. The resulting open loop of saw chain can fracture a second time and create a projectile consisting of several saw-chain links referred to as a chain shot. Its high kinetic energy enables it to penetrate operator enclosures and be a significant hazard. Accurate data on projectile composition, mass, and speed are needed for the design of both operator enclosures resistant to projectile penetration and for saw chain resistant to fracture. The work presented here contributes to providing this data through the use of a test machine designed and built at Oregon State University. The machine’s enclosure is a standard shipping container. To safely contain any anticipated chain shot, the container was lined with both 9.5 mm AR500 steel plates and 50 mm high-density polyethylene (HDPE). During normal operation, projectiles are captured virtually undamaged in the HDPE enabling subsequent analysis. Standard harvester components are used for bar mounting and chain tensioning. Standard guide bars and saw chains are used. An electric motor with flywheel drives the system. Testing procedures follow ISO Standard 11837. Chain speed at break was approximately 45.5 m/s. Data was collected using both a 75 cm solid bar (Oregon 752HSFB149) and 90 cm solid bar (Oregon 902HSFB149). Saw chains used were 89 Drive Link .404”-18HX loops made from factory spools. Standard 16-tooth sprockets were used. Projectile speed was measured using both a high-speed camera and a chronograph. Both rotational and translational kinetic energy are calculated. For this study 50 chain shot events were executed. Results showed that projectiles consisted of a variety combinations of drive links, tie straps, and cutter links. Most common (occurring in 60% of the events) was a drive-link / tie-strap / drive-link combination having a mass of approximately 10.33 g. Projectile mass varied from a minimum of 2.99 g corresponding to a drive link only to a maximum of 18.91 g corresponding to a drive-link / tie-strap / drive-link / cutter-link / drive-link combination. Projectile translational speed was measured to be approximately 270 m/s and rotational speed of approximately 14000 r/s. The calculated translational and rotational kinetic energy magnitudes each average over 600 J. This study provides useful information for both timber harvester manufacturers and saw chain manufacturers to design products that reduce the hazards associated with timber harvesting.

Keywords: chain shot, timber harvesters, safety, testing

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Authors: Andrew Kurochkin, Kostiantyn Bokhan

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In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Jose D. Herrera, Mario A. Rios

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This paper deals with the coordinated tuning of the Power System Stabilizer (PSS) controller and Power Oscillation Damping (POD) Controller of Flexible AC Transmission System (FACTS) in a multi-machine power systems. The coordinated tuning is based on the critical eigenvalues of the power system and a model reduction technique where the Hankel Singular Value method is applied. Through the linearized system model and the parameter-constrained nonlinear optimization algorithm, it can compute the parameters of both controllers. Moreover, the parameters are optimized simultaneously obtaining the gains of both controllers. Then, the nonlinear simulation to observe the time response of the controller is performed.

Keywords: electromechanical oscillations, power system stabilizers, power oscillation damping, hankel singular values

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Authors: Steven Hidalgo, Patricio Neumann

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The growth of societies has increased the consumption of raw materials and food obtained from nature. This has influenced the services offered by ecosystems to humans, mainly supply and regulation services. One of the indicators used to evaluate these services is Net Primary Productivity (NPP), which is understood as the energy stored in the form of biomass by primary organisms through the process of photosynthesis and respiration. The variation of NPP by defined area produces changes in the properties of terrestrial and aquatic ecosystems, which alter factors such as biodiversity, nutrient cycling, carbon storage and water quality. The analysis of NPP to evaluate variations in ecosystem services includes harvested NPP (understood as provisioning services), which is the raw material from agricultural systems used by humans as a source of energy and food, and the remaining NPP (expressed as a regulating service) or the amount of biomass that remains in ecosystems after the harvesting process, which is mainly related to factors such as biodiversity. Given that agriculture is a fundamental pillar of Chile's integral development, the purpose of this study is to evaluate provisioning and regulating ecosystem services in the agricultural sector, specifically in cereal production, in the communes of the central-southern regions of Chile through a conceptual framework based on the quantification of the fraction of Human Appropriation of Net Primary Productivity (HANPP) and the fraction remaining in the ecosystems (NPP remaining). A total of 161 communes were analyzed in the regions of O'Higgins, Maule, Ñuble, Bio-Bío, La Araucanía and Los Lagos, which are characterized by having the largest areas planted with cereals. It was observed that the region of La Araucanía produces the greatest amount of dry matter, understood as provisioning service, where Victoria is the commune with the highest cereal production in the country. In addition, the maximum value of HANPP was in the O'Higgins region, highlighting the communes of Coltauco, Quinta de Tilcoco, Placilla and Rengo. On the other hand, the communes of Futrono, Pinto, Lago Ranco and Pemuco, whose cereal production was important during the study, had the highest values of remaining NPP as a regulating service. Finally, an inverse correlation was observed between the provisioning and regulating ecosystem services, i.e., the higher the cereal or dry matter production in a defined area, the lower the net primary production remaining in the ecosystems. Based on this study, future research will focus on the evaluation of ecosystem services associated with other crops, such as forestry plantations, whose activity is an important part of the country's productive sector.

Keywords: provisioning services, regulating services, net primary productivity, agriculture

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Authors: Mohsen Rabbani, Trista McLaughlin, Ehsan Vahidi

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the remediation of polluted sites with heavy metals, such as rare earth elements (REEs), has been a primary concern of researchers to decontaminate the soil. Among all developed methods to address this concern, phytoremediation has been established as efficient, cost-effective, easy-to-use, and environmentally friendly way, providing a long-term solution for addressing this global concern. Furthermore, this technology has another great potential application in the metals production sector through returning metals buried in soil via metals cropping. Considering the significant metal concentration in hyper-accumulators, the utilization of bioaccumulated metals to extract metals from plant matter has been proposed as a sub-economic area called phytomining. As a recent, more advanced technology to eliminate such pollutants from the soil and produce critical metals, bioharvesting (phytomining/agromining) has been considered another compromising way to produce metals and meet the global demand for critical/target metals. The bio-ore obtained from phytomining can be safely disposed of or introduced to metal production pathways to obtain the most demanded metals, such as REEs. It is well-known that some hyperaccumulators, e.g., fern Dicranopteris linearis, can be used to absorb REE metals from the polluted soils and accumulate them in plant organs, such as leaves and stems. After soil remediation, the plant species can be harvested and introduced to the downstream steps, namely crushing/grinding, leaching, and purification processes, to extract REEs from plant matter. This novel interdisciplinary field can fill the gap between agriculture, mining, metallurgy, and the environment. Despite the advantages of agromining for the REEs production industry, key issues related to the environmental sustainability of the entire life cycle of this new concept have not been assessed yet. Hence, a comparative life cycle assessment (LCA) study was conducted to quantify the environmental footprints of REEs phytomining. The current LCA study aims to estimate and calculate environmental effects associated with phytomining by considering critical factors, such as climate change, land use, and ozone depletion. The results revealed that phytomining is an easy-to-use and environmentally sustainable approach to either eliminate REEs from polluted sites or produce REEs, offering a new source of such metals production. This LCA research provides guidelines for researchers active in developing a reliable relationship between agriculture, mining, metallurgy, and the environment to encounter soil pollution and keep the earth green and clean.

Keywords: phytoremediation, phytomining, life cycle assessment, environmental impacts, rare earth elements, hyperaccumulator

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Authors: Mohamed Moustafa Mahmoud Sedky

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In line start permanent magnet synchronous motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. This paper presents an FEM that identifies different models, static eccentricity, dynamic eccentricity, and mixed eccentricity, at no load and full load. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates motor speed, torque and flux density distribution along the air gap for SE, DE, and ME. This paper represents the various effects of different eccentricities types on the transient performance.

Keywords: line start permanent magnet, synchronous machine, static eccentricity, dynamic eccentricity, mixed eccentricity

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Authors: Jaskirat Singh, Roshan Lal Virdi, Khushdeep Goyal

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The purpose of this paper is to perform a microstructural analysis of Friction Stir Welded joints of aluminum alloys 6063 and 5083, also to check the properties of the weld zone by SEM analysis. FSW experiments were carried on CNC Vertical milling machine. The tools used for welding were the round cylindrical pin shape and square pin shape. It is found that Microstructure shows the uniformly distributed material with minimum heat affected zone and dense welded zone without any defect. Microstructures indicate that the weld material is defect free. The SEM shows the diffusion of material with base metal with proper bonding without any defect.

Keywords: friction stir welding, aluminum alloy, microstructure, SEM analysis

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Rupan Preet Kaur

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This article reviewed the potential of artificial intelligence in the field of identity and access management (IAM) and identity governance and administration (IGA), the most critical pillars of any organization. The power of leveraging AI in the most complex and huge user base environment was outlined by simplifying and streamlining the user access approvals and re-certifications without any impact on the user productivity and at the same time strengthening the overall compliance of IAM landscape. Certain challenges encountered in the current state were detailed where majority of organizations are still lacking maturity in the data integrity aspect. Finally, this paper concluded that within the realm of possibility, users and application owners can reap the benefits of unified approach provided by AI to improve the user experience, improve overall efficiency, and strengthen the risk posture.

Keywords: artificial intelligence, machine learning, user access review, access approval

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

Abstract:

This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: G. Bravo, D. Lopez, A. Iriarte

Abstract:

Several organizations and governments have created a demand for information about the environmental impacts of agricultural products. Today, the export oriented fruit sector in Chile is being challenged to quantify and reduce their environmental impacts. Chile is the largest southern hemisphere producer and exporter of sweet cherry fruit. Chilean sweet cherry production reached a volume of 80,000 tons in 2012. The main destination market for the Chilean cherry in 2012 was Asia (including Hong Kong and China), taking in 69% of exported volume. Another important market was the United States with 16% participation, followed by Latin America (7%) and Europe (6%). Concerning geographical distribution, the Chilean conventional cherry production is focused in the center-south area, between the regions of Maule and O’Higgins; both regions represent 81% of the planted surface. The Life Cycle Assessment (LCA) is widely accepted as one of the major methodologies for assessing environmental impacts of products or services. The LCA identifies the material, energy, material, and waste flows of a product or service, and their impact on the environment. There are scant studies that examine the impacts of sweet cherry cultivation, such as acidification and eutrophication. Within this context, the main objective of this study is to evaluate, using the LCA, the acidification and eutrophication impacts of sweet cherry production in Chile. The additional objective is to identify the agricultural inputs that contributed significantly to the impacts of this fruit. The system under study included all the life cycle stages from the cradle to the farm gate (harvested sweet cherry). The data of sweet cherry production correspond to nationwide representative practices and are based on technical-economic studies and field information obtained in several face-to-face interviews. The study takes into account the following agricultural inputs: fertilizers, pesticides, diesel consumption for agricultural operations, machinery and electricity for irrigation. The results indicated that the mineral fertilizers are the most important contributors to the acidification and eutrophication impacts of the sheet cherry cultivation. Improvement options are suggested for the hotspot in order to reduce the environmental impacts. The results allow planning and promoting low impacts procedures across fruit companies, as well as policymakers, and other stakeholders on the subject. In this context, this study is one of the first assessments of the environmental impacts of sweet cherry production. New field data or evaluation of other life cycle stages could further improve the knowledge on the impacts of this fruit. This study may contribute to environmental information in other countries where there is similar agricultural production for sweet cherry.

Keywords: acidification, eutrophication, life cycle assessment, sweet cherry production

Procedia PDF Downloads 255

Authors: Santhosh Kumat T., Priya E.

Abstract:

The control of a doubly fed induction generator by fuzzy is described. The active and reactive power can be controlled by rotor and grid side converters with fuzzy controller. The main objective is to maintain constant voltage and frequency at the output of the generator. However the Line Side Converter (LSC) can be controlled to supply up to 50% of the required reactive current. When the crowbar is not activated the DFIG can supply reactive power from the rotor side through the machine as well as through the LSC.

Keywords: Doubly Fed Induction Generator (DFIG), Rotor Side Converter (RSC), Grid Side Converter (GSC), Wind Energy Conversion Systems (WECS)

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Authors: Silvia Portarena, Chiara Anselmi, Chiara Baldacchini, Enrico Brugnoli

Abstract:

Extra virgin olive oil (EVOO) is a complex matrix mainly composed by fatty acid and other minor compounds, among which carotenoids are well known for their antioxidative function that is a key mechanism of protection against cancer, cardiovascular diseases, and macular degeneration in humans. EVOO composition in terms of such constituents is generally the result of a complex combination of genetic, agronomical and environmental factors. To selectively improve the quality of EVOOs, the role of each factor on its biochemical composition need to be investigated. By selecting fruits from four different cultivars similarly grown and harvested, it was demonstrated that Raman spectroscopy, combined with chemometric analysis, is able to discriminate the different cultivars, also as a function of the harvest date, based on the relative content and composition of fatty acid and carotenoids. In particular, a correct classification up to 94.4% of samples, according to the cultivar and the maturation stage, was obtained. Moreover, by using gas chromatography and high-performance liquid chromatography as reference techniques, the Raman spectral features further allowed to build models, based on partial least squares regression, that were able to predict the relative amount of the main fatty acids and the main carotenoids in EVOO, with high coefficients of determination. Besides genetic factors, climatic parameters, such as light exposition, distance from the sea, temperature, and amount of precipitations could have a strong influence on EVOO composition of both major and minor compounds. This suggests that the Raman spectra could act as a specific fingerprint for the geographical discrimination and authentication of EVOO. To understand the influence of environment on EVOO Raman spectra, samples from seven regions along the Italian coasts were selected and analyzed. In particular, it was used a dual approach combining Raman spectroscopy and isotope ratio mass spectrometry (IRMS) with principal component and linear discriminant analysis. A correct classification of 82% EVOO based on their regional geographical origin was obtained. Raman spectra were obtained by Super Labram spectrometer equipped with an Argon laser (514.5 nm wavelenght). Analyses of stable isotope content ratio were performed using an isotope ratio mass spectrometer connected to an elemental analyzer and to a pyrolysis system. These studies demonstrate that RR spectroscopy is a valuable and useful technique for the analysis of EVOO. In combination with statistical analysis, it makes possible the assessment of specific samples’ content and allows for classifying oils according to their geographical and varietal origin.

Keywords: authentication, chemometrics, olive oil, raman spectroscopy

Procedia PDF Downloads 313