Search results for: large PV power plant
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15307

Search results for: large PV power plant

12247 Development of A MG-Gd-Er-Zn-Zr Alloy with Ultrahigh Strength and Ductility via Extrusion, Pre-Deformation, and Two-Stage Aging

Authors: Linyue Jia, Wenbo Du, Zhaohui Wang, Ke Liu, Shubo Li

Abstract:

Due to the great potential for weight reduction in aerospace and automotive industries, magnesium-rare earth (Mg-RE) based alloys with outstanding mechanical performance have been widely investigated for decades. However, magnesium alloys are still restricted in engineering applications because of their lower strength and ductility. Hence, there are large spaces and challenges in achieving high-performance Mg alloys. This work reports an Mg-Gd-Er-Zn-Zr alloy with ultrahigh strength and good ductility developed via hot extrusion, pre-deformation, and two-stage aging. The extruded alloy comprises fine dynamically recrystallized (DRXed) grains and coarse worked grains with a large aspect ratio. Pre-deformation has little effect on the microstructure and macro-texture and serves primarily to introduce a large number of dislocations, resulting in strain hardening and higher precipitation strengthening during subsequent aging due to more nucleation sites. As a result, the alloy exhibits a yield strength (YS) of 506 MPa, an ultimate tensile strength (UTS) of 549 MPa, and elongation (EL) of 8.2% at room temperature, showing superior strength-ductility balance than the other wrought Mg-RE alloys previously reported. The current study proposes a combination of pre-deformation and two-stage aging to further improve the mechanical properties of wrought Mg alloys for engineering applications.

Keywords: magnesium alloys, mechanical properties, microstructure, pre-deformation, two-stage aging

Procedia PDF Downloads 165
12246 Aerodynamic Design Optimization Technique for a Tube Capsule That Uses an Axial Flow Air Compressor and an Aerostatic Bearing

Authors: Ahmed E. Hodaib, Muhammed A. Hashem

Abstract:

High-speed transportation has become a growing concern. To increase high-speed efficiencies and minimize power consumption of a vehicle, we need to eliminate the friction with the ground and minimize the aerodynamic drag acting on the vehicle. Due to the complexity and high power requirements of electromagnetic levitation, we make use of the air in front of the capsule, that produces the majority of the drag, to compress it in two phases and inject a proportion of it through small nozzles to make a high-pressure air cushion to levitate the capsule. The tube is partially-evacuated so that the air pressure is optimized for maximum compressor effectiveness, optimum tube size, and minimum vacuum pump power consumption. The total relative mass flow rate of the tube air is divided into two fractions. One is by-passed to flow over the capsule body, ensuring that no chocked flow takes place. The other fraction is sucked by the compressor where it is diffused to decrease the Mach number (around 0.8) to be suitable for the compressor inlet. The air is then compressed and intercooled, then split. One fraction is expanded through a tail nozzle to contribute to generating thrust. The other is compressed again. Bleed from the two compressors is used to maintain a constant air pressure in an air tank. The air tank is used to supply air for levitation. Dividing the total mass flow rate increases the achievable speed (Kantrowitz limit), and compressing it decreases the blockage of the capsule. As a result, the aerodynamic drag on the capsule decreases. As the tube pressure decreases, the drag decreases and the capsule power requirements decrease, however, the vacuum pump consumes more power. That’s why Design optimization techniques are to be used to get the optimum values for all the design variables given specific design inputs. Aerodynamic shape optimization, Capsule and tube sizing, compressor design, diffuser and nozzle expander design and the effect of the air bearing on the aerodynamics of the capsule are to be considered. The variations of the variables are to be studied for the change of the capsule velocity and air pressure.

Keywords: tube-capsule, hyperloop, aerodynamic design optimization, air compressor, air bearing

Procedia PDF Downloads 330
12245 Monitoring Large-Coverage Forest Canopy Height by Integrating LiDAR and Sentinel-2 Images

Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

Abstract:

Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

Procedia PDF Downloads 92
12244 Detection of Cytotoxicity of Green Synthesized Silver, Gold, and Silver/Gold Bimetallic on Baby Hamster Kidney-21 Cells Using MTT Assay

Authors: Naila Sher, Mushtaq Ahmed, Nadia Mushtaq, Rahmat Ali Khan

Abstract:

In cancer therapy, nanoparticles (NPs) shall be applied possibly by inoculation in the veins of humans. This action will connect them with white (WBCs) and red blood cells (RBCs) in the bloodstream before they reach their main targeted cancer cells. However, possible effects of silver, gold, and silver/gold bimetallic NPs (Ag, Au, and Ag/Au BNPs) on baby hamster kidney-21 (BHK-21) cells were studied by MTT assay. Here, Ag, Au, and their Ag/Au BNPs (bimetallic nanoparticles) were synthesized by using Hippeastrum hybridum (HH) extract. These NPs were characterized by UV-visible spectroscopy, FT-IR, XRD, and EDX, and SEM analysis. XRD analysis conferring the crystal structure with an average size of 13.3, 10.72, and 8.34nm of Ag, Au, and Ag/Au BNPs, respectively. SEM showed that Ag, Au, and Ag/Au BNPs had irregular morphologies, with nano measures calculated sizes of 40, 30, and 20 nm respectively. EDX spectrometers confirmed the presence of elemental Ag signal of the AgNPs with 22.75%, Au signal of the AuNPs with 48.08%, Ag signal with 12%, and Au signal with 38.26% of the Ag/Au BNPs. The BHK-21cells were incubated in the existence of doxorubicin, plant extract, Ag, Au, and Ag/Au BNPs. The cytotoxic effects could be observed in a dose-dependent mode; doxorubicin and Ag/Au BNPs were more toxic than plant extract, Ag, and Au NPs. It is demonstrated that NPs interact with BHK-21cells and significantly reduce cell viability in a concentration-dependent manner. However, to reduce the potential threats of NPs further studies are recommended.

Keywords: hippeastrum hybridum, nanoparticle, BHK-21cells

Procedia PDF Downloads 133
12243 The Reliability and Shape of the Force-Power-Velocity Relationship of Strength-Trained Males Using an Instrumented Leg Press Machine

Authors: Mark Ashton Newman, Richard Blagrove, Jonathan Folland

Abstract:

The force-velocity profile of an individual has been shown to influence success in ballistic movements, independent of the individuals' maximal power output; therefore, effective and accurate evaluation of an individual’s F-V characteristics and not solely maximal power output is important. The relatively narrow range of loads typically utilised during force-velocity profiling protocols due to the difficulty in obtaining force data at high velocities may bring into question the accuracy of the F-V slope along with predictions pertaining to the maximum force that the system can produce at a velocity of null (F₀) and the theoretical maximum velocity against no load (V₀). As such, the reliability of the slope of the force-velocity profile, as well as V₀, has been shown to be relatively poor in comparison to F₀ and maximal power, and it has been recommended to assess velocity at loads closer to both F₀ and V₀. The aim of the present study was to assess the relative and absolute reliability of an instrumented novel leg press machine which enables the assessment of force and velocity data at loads equivalent to ≤ 10% of one repetition maximum (1RM) through to 1RM during a ballistic leg press movement. The reliability of maximal and mean force, velocity, and power, as well as the respective force-velocity and power-velocity relationships and the linearity of the force-velocity relationship, were evaluated. Sixteen male strength-trained individuals (23.6 ± 4.1 years; 177.1 ± 7.0 cm; 80.0 ± 10.8 kg) attended four sessions; during the initial visit, participants were familiarised with the leg press, modified to include a mounted force plate (Type SP3949, Force Logic, Berkshire, UK) and a Micro-Epsilon WDS-2500-P96 linear positional transducer (LPT) (Micro-Epsilon, Merseyside, UK). Peak isometric force (IsoMax) and a dynamic 1RM, both from a starting position of 81% leg length, were recorded for the dominant leg. Visits two to four saw the participants carry out the leg press movement at loads equivalent to ≤ 10%, 30%, 50%, 70%, and 90% 1RM. IsoMax was recorded during each testing visit prior to dynamic F-V profiling repetitions. The novel leg press machine used in the present study appears to be a reliable tool for measuring F and V-related variables across a range of loads, including velocities closer to V₀ when compared to some of the findings within the published literature. Both linear and polynomial models demonstrated good to excellent levels of reliability for SFV and F₀ respectively, with reliability for V₀ being good using a linear model but poor using a 2nd order polynomial model. As such, a polynomial regression model may be most appropriate when using a similar unilateral leg press setup to predict maximal force production capabilities due to only a 5% difference between F₀ and obtained IsoMax values with a linear model being best suited to predict V₀.

Keywords: force-velocity, leg-press, power-velocity, profiling, reliability

Procedia PDF Downloads 58
12242 Remotely Sensed Data Fusion to Extract Vegetation Cover in the Cultural Park of Tassili, South of Algeria

Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

Abstract:

The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

Procedia PDF Downloads 433
12241 Potential of Salvia sclarea L. for Phytoremediation of Soils Contaminated with Heavy Metals

Authors: Violina R. Angelova, Radka V. Ivanova, Givko M. Todorov, Krasimir I. Ivanov

Abstract:

A field study was conducted to evaluate the efficacy of Salvia sclarea L. for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The content of heavy metals in different parts of Salvia sclarea L. (roots, stems, leaves and inflorescences) was determined by ICP. The essential oil of the Salvia sclarea L. was obtained by steam distillation in laboratory conditions and was analyzed for heavy metals and its chemical composition was determined. Salvia sclarea L. is a plant which is tolerant to heavy metals and can be grown on contaminated soils. Based on the obtained results and using the most common criteria, Salvia sclarea L. can be classified as Pb hyperaccumulator and Cd and Zn accumulators, therefore, this plant has suitable potential for the phytoremediation of heavy metal contaminated soils. Favorable is also the fact that heavy metals do not influence the development of the Salvia sclarea L., as well as on the quality and quantity of the essential oil. For clary sage oil obtained from the processing of clary sage grown on highly contaminated soils, its key odour-determining ingredients meet the quality requirements of the European Pharmacopoeia and BS ISO 7609 regarding Bulgarian clary sage oil and/or have values that are close to the limits of these standards. The possibility of further industrial processing will make Salvia sclarea L. an economically interesting crop for farmers of phytoextraction technology.

Keywords: clary sage, heavy metals, phytoremediation, polluted soils

Procedia PDF Downloads 216
12240 Improving Fingerprinting-Based Localization System Using Generative AI

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 42
12239 Automatic Detection of Sugarcane Diseases: A Computer Vision-Based Approach

Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

Abstract:

The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

Procedia PDF Downloads 116
12238 Hydrothermal Synthesis of Hydrosodalite by Using Ultrasounds

Authors: B. Białecka, Z. Adamczyk, M. Cempa

Abstract:

The use of ultrasounds in zeolization of fly ash can increase the efficiency of this process. The molar ratios of the reagents, as well as the time and temperature of the synthesis, are the main parameters determining the type and properties of the zeolite formed. The aim of the work was to create hydrosodalite in a short time (8h), with low NaOH concentration (3 M) and in low temperature (80°C). A zeolite material contained in fly ash from hard coal combustion in one of Polish Power Plant was subjected to hydrothermal alkaline synthesis. The phase composition of the ash consisted mainly of glass, mullite, quartz, and hematite. The dominant chemical components of the ash were SiO₂ (over 50%mas.) and Al₂O₃ (more than 28%mas.), whereas the contents of the remaining components, except Fe₂O₃ (6.34%mas.), did not exceed 4% mas. The hydrothermal synthesis of the zeolite material was carried out in the following conditions: 3M-solution of NaOH, synthesis time – 8 hours, 40 kHz-frequency ultrasounds during the first two hours of synthesis. The mineral components of the input ash as well as product after synthesis were identified in microscopic observations, in transmitted light, using X-ray diffraction (XRD) and electron scanning microscopy (SEM/EDS). The chemical composition of the input ash was identified by the method of X-ray fluorescence (XRF). The obtained material apart from phases found in the initial fly ash sample, also contained new phases, i.e., hydrosodalite and NaP-type zeolite. The chemical composition in micro areas of grains indicated their diversity: i) SiO₂ content was in the range 30-59%mas., ii) Al₂O₃ content was in the range 24-35%mas., iii) Na₂O content was in the range 6-15%mas. This clearly indicates that hydrosodalite forms hypertrophies with NaP type zeolite as well as relict grains of fly ash. A small amount of potassium in the examined grains is noteworthy, which may indicate the substitution of sodium with potassium. This is confirmed by the high value of the correlation coefficient between these two components.

Keywords: fly ash, hydrosodalite, ultrasounds, zeolite

Procedia PDF Downloads 152
12237 Application of Particle Swarm Optimization to Thermal Sensor Placement for Smart Grid

Authors: Hung-Shuo Wu, Huan-Chieh Chiu, Xiang-Yao Zheng, Yu-Cheng Yang, Chien-Hao Wang, Jen-Cheng Wang, Chwan-Lu Tseng, Joe-Air Jiang

Abstract:

Dynamic Thermal Rating (DTR) provides crucial information by estimating the ampacity of transmission lines to improve power dispatching efficiency. To perform the DTR, it is necessary to install on-line thermal sensors to monitor conductor temperature and weather variables. A simple and intuitive strategy is to allocate a thermal sensor to every span of transmission lines, but the cost of sensors might be too high to bear. To deal with the cost issue, a thermal sensor placement problem must be solved. This research proposes and implements a hybrid algorithm which combines proper orthogonal decomposition (POD) with particle swarm optimization (PSO) methods. The proposed hybrid algorithm solves a multi-objective optimization problem that concludes the minimum number of sensors and the minimum error on conductor temperature, and the optimal sensor placement is determined simultaneously. The data of 345 kV transmission lines and the hourly weather data from the Taiwan Power Company and Central Weather Bureau (CWB), respectively, are used by the proposed method. The simulated results indicate that the number of sensors could be reduced using the optimal placement method proposed by the study and an acceptable error on conductor temperature could be achieved. This study provides power companies with a reliable reference for efficiently monitoring and managing their power grids.

Keywords: dynamic thermal rating, proper orthogonal decomposition, particle swarm optimization, sensor placement, smart grid

Procedia PDF Downloads 432
12236 Tax Competition and Partial Tax Coordination under Fiscal Decentralization

Authors: Patricia Sanz-Cordoba, Bernd Theilen

Abstract:

This article analyzes the conditions where decentralization and partial tax harmonization in a coalition of asymmetric jurisdictions plays a role in the fight of fiscal competition (i.e. the race to bottom). Starting from a centralized economies, we use the ZM-W model to analyze the fiscal competition and coordination among three countries. We find that the asymmetry of jurisdictions facilitates partial tax harmonization between jurisdictions when these asymmetries are not too large. Furthermore, when the asymmetries are large enough, the level of labor tax plays an important role in the decision of decentralize capital tax. Accordingly, decentralization is achievable when labor tax is low. This result indicates that decentralization and partial tax harmonization between jurisdictions can be possible results in order to fight the negative externalities from fiscal competition, and more in the European Union countries where the asymmetries are substantial.

Keywords: centralization, decentralization, fiscal competition, partial tax harmonization

Procedia PDF Downloads 245
12235 Cytotoxic Activity of Parkia javanica Merr. and Parkia speciosa Hassk. against Human Cancer Cell Lines

Authors: Srisopa Ruangnoo, Arunporn Itharat

Abstract:

The ethanolic and aqueous extracts of Parkia javanica Merr. germinating seeds and Parkia speciosa Hassk. seeds were evaluated for cytotoxic activity against three different types of human cancer cell lines including colon cancer (LS174T), breast cancer (MCF-7) and prostate cancer (PC3) using sulforhodamine B (SRB) assay. The fresh plant parts were divided into 2 parts. The first part was extracted by maceration with 95% ethanol for 3 days and then filtered, and the filtrates were evaporated by rotary evaporator. The other part was squeezed and filtered. Then the filtrates were dried by freeze dryer. The screening found that the aqueous extract of P. javanica Merr. germinating seeds exhibited more than 70% inhibition (at concentration 50 µg/ml) against all types of human cancer cells. The aqueous extract of P. javanica Merr. germinating seeds showed the highest cytotoxic activity against MCF-7 with the IC50 value as 5.63 µg/ml. The aqueous extract of P. javanica Merr. germinating seeds also showed high cytotoxic activity against PC3 and LS174T with the IC50 values as 10.79 and 11.40 µg/ml, respectively. In conclusion, P. javanica Merr. germinating seed is a natural source of anticancer activity and further research to isolate active compounds from this plant should be undertaken.

Keywords: cytotoxic activity, Parkia javanica Merr., Parkia speciosa Hassk., human cancer cell lines

Procedia PDF Downloads 408
12234 Geometric Optimisation of Piezoelectric Fan Arrays for Low Energy Cooling

Authors: Alastair Hales, Xi Jiang

Abstract:

Numerical methods are used to evaluate the operation of confined face-to-face piezoelectric fan arrays as pitch, P, between the blades is varied. Both in-phase and counter-phase oscillation are considered. A piezoelectric fan consists of a fan blade, which is clamped at one end, and an extremely low powered actuator. This drives the blade tip’s oscillation at its first natural frequency. Sufficient blade tip speed, created by the high oscillation frequency and amplitude, is required to induce vortices and downstream volume flow in the surrounding air. A single piezoelectric fan may provide the ideal solution for low powered hot spot cooling in an electronic device, but is unable to induce sufficient downstream airflow to replace a conventional air mover, such as a convection fan, in power electronics. Piezoelectric fan arrays, which are assemblies including multiple fan blades usually in face-to-face orientation, must be developed to widen the field of feasible applications for the technology. The potential energy saving is significant, with a 50% power demand reduction compared to convection fans even in an unoptimised state. A numerical model of a typical piezoelectric fan blade is derived and validated against experimental data. Numerical error is found to be 5.4% and 9.8% using two data comparison methods. The model is used to explore the variation of pitch as a function of amplitude, A, for a confined two-blade piezoelectric fan array in face-to-face orientation, with the blades oscillating both in-phase and counter-phase. It has been reported that in-phase oscillation is optimal for generating maximum downstream velocity and flow rate in unconfined conditions, due at least in part to the beneficial coupling between the adjacent blades that leads to an increased oscillation amplitude. The present model demonstrates that confinement has a significant detrimental effect on in-phase oscillation. Even at low pitch, counter-phase oscillation produces enhanced downstream air velocities and flow rates. Downstream air velocity from counter-phase oscillation can be maximally enhanced, relative to that generated from a single blade, by 17.7% at P = 8A. Flow rate enhancement at the same pitch is found to be 18.6%. By comparison, in-phase oscillation at the same pitch outputs 23.9% and 24.8% reductions in peak downstream air velocity and flow rate, relative to that generated from a single blade. This optimal pitch, equivalent to those reported in the literature, suggests that counter-phase oscillation is less affected by confinement. The optimal pitch for generating bulk airflow from counter-phase oscillation is large, P > 16A, due to the small but significant downstream velocity across the span between adjacent blades. However, by considering design in a confined space, counterphase pitch should be minimised to maximise the bulk airflow generated from a certain cross-sectional area within a channel flow application. Quantitative values are found to deviate to a small degree as other geometric and operational parameters are varied, but the established relationships are maintained.

Keywords: piezoelectric fans, low energy cooling, power electronics, computational fluid dynamics

Procedia PDF Downloads 221
12233 The Effect of Annual Weather and Sowing Date on Different Genotype of Maize (Zea mays L.) in Germination and Yield

Authors: Ákos Tótin

Abstract:

In crop production the most modern hybrids are available for us, therefore the yield and yield stability is determined by the agro-technology. The purpose of the experiment is to adapt the modern agrotechnology to the new type of hybrids. The long-term experiment was set up in 2015-2016 on chernozem soil in the Hajdúság (eastern Hungary). The plots were set up in 75 thousand ha-1 plant density. We examined some mainly use hybrids of Hungary. The conducted studies are: germination dynamic, growing dynamic and the effect of annual weather for the yield. We use three different sowing date as early, average and late, and measure how many plant germinated during the germination process. In the experiment, we observed the germination dynamics in 6 hybrid in 4 replication. In each replication, we counted the germinated plants in 2m long 2 row wide area. Data will be shown in the average of the 6 hybrid and 4 replication. Growing dynamics were measured from the 10cm (4-6 leaf) plant highness. We measured 10 plants’ height in two weeks replication. The yield was measured buy a special plot harvester - the Sampo Rosenlew 2010 – what measured the weight of the harvested plot and also took a sample from it. We determined the water content of the samples for the water release dynamics. After it, we calculated the yield (t/ha) of each plot at 14% of moisture content to compare them. We evaluated the data using Microsoft Excel 2015. The annual weather in each crop year define the maize germination dynamics because the amount of heat is determinative for the plants. In cooler crop year the weather is prolonged the germination. At the 2015 crop year the weather was cold in the beginning what prolonged the first sowing germination. But the second and third sowing germinated faster. In the 2016 crop year the weather was much favorable for plants so the first sowing germinated faster than in the previous year. After it the weather cooled down, therefore the second and third sowing germinated slower than the last year. The statistical data analysis program determined that there is a significant difference between the early and late sowing date growing dynamics. In 2015 the first sowing date had the highest amount of yield. The second biggest yield was in the average sowing time. The late sowing date has lowest amount of yield.

Keywords: germination, maize, sowing date, yield

Procedia PDF Downloads 231
12232 Energy Management System and Interactive Functions of Smart Plug for Smart Home

Authors: Win Thandar Soe, Innocent Mpawenimana, Mathieu Di Fazio, Cécile Belleudy, Aung Ze Ya

Abstract:

Intelligent electronic equipment and automation network is the brain of high-tech energy management systems in critical role of smart homes dominance. Smart home is a technology integration for greater comfort, autonomy, reduced cost, and energy saving as well. These services can be provided to home owners for managing their home appliances locally or remotely and consequently allow them to automate intelligently and responsibly their consumption by individual or collective control systems. In this study, three smart plugs are described and one of them tested on typical household appliances. This article proposes to collect the data from the wireless technology and to extract some smart data for energy management system. This smart data is to quantify for three kinds of load: intermittent load, phantom load and continuous load. Phantom load is a waste power that is one of unnoticed power of each appliance while connected or disconnected to the main. Intermittent load and continuous load take in to consideration the power and using time of home appliances. By analysing the classification of loads, this smart data will be provided to reduce the communication of wireless sensor network for energy management system.

Keywords: energy management, load profile, smart plug, wireless sensor network

Procedia PDF Downloads 273
12231 Language and Power Relations in Selected Political Crisis Speeches in Nigeria: A Critical Discourse Analysis

Authors: Isaiah Ifeanyichukwu Agbo

Abstract:

Human speech is capable of serving many purposes. Power and control are not always exercised overtly by linguistic acts, but maybe enacted and exercised in the myriad of taken-for-granted actions of everyday life. Domination, power control, discrimination and mind control exist in human speech and may lead to asymmetrical power relations. In discourse, there are persuasive and manipulative linguistic acts that serve to establish solidarity and identification with the 'we group' and polarize with the 'they group'. Political discourse is crafted to defend and promote the problematic narrative of outright controversial events in a nation’s history thereby sustaining domination, marginalization, manipulation, inequalities and injustices, often without the dominated and marginalized group being aware of them. They are designed and positioned to serve the political and social needs of the producers. Political crisis speeches in Nigeria, just like in other countries concentrate on positive self-image, de-legitimization of political opponents, reframing accusation to one’s advantage, redefining problematic terms and adopting reversal strategy. In most cases, the people are ignorant of the hidden ideological positions encoded in the text. Few researches have been conducted adopting the frameworks of critical discourse analysis and systemic functional linguistics to investigate this situation in the political crisis speeches in Nigeria. In this paper, we focus attention on the analyses of the linguistic, semantic, and ideological elements in selected political crisis speeches in Nigeria to investigate if they create and sustain unequal power relations and manipulative tendencies from the perspectives of Critical Discourse Analysis (CDA) and Systemic Functional Linguistics (SFL). Critical Discourse Analysis unpacks both opaque and transparent structural relationships of power dominance, power relations and control as manifested in language. Critical discourse analysis emerged from a critical theory of language study which sees the use of language as a form of social practice where social relations are reproduced or contested and different interests are served. Systemic function linguistics relates the structure of texts to their function. Fairclough’s model of CDA and Halliday’s systemic functional approach to language study are adopted in this paper. This paper probes into language use that perpetuates inequalities. This study demystifies the hidden implicature of the selected political crisis speeches and reveals the existence of information that is not made explicit in what the political actors actually say. The analysis further reveals the ideological configurations present in the texts. These ideological standpoints are the basis for naturalizing implicit ideologies and hegemonic influence in the texts. The analyses of the texts further uncovered the linguistic and discursive strategies deployed by text producers to manipulate the unsuspecting members of the public both mentally and conceptually in order to enact, sustain and maintain unhealthy power relations at crisis times in the Nigerian political history.

Keywords: critical discourse analysis, language, political crisis, power relations, systemic functional linguistics

Procedia PDF Downloads 342
12230 Basil Plants Attract and Benefit Generalist Lacewing Predator Ceraeochrysa cubana Hagen (Neuroptera: Chrysopidae) by Providing Nutritional Resources

Authors: Michela C. Batista Matos, Madelaine Venzon, Elem F. Martins, Erickson C. Freitas, Adenir V. Teodoro, Maira C. M. Fonseca, Angelo Pallini

Abstract:

Aromatic plant species are capable of producing and releasing volatile organic compounds spontaneously, which can repel or attract beneficial insects such as generalist predators of herbivores. Attractive plants could be used as crop companion plants to promote biological control of pests. In order to select such plants for future use in horticulture fields, we assessed the attractiveness of the aromatic plants Ocimum basilicum L. (basil), Mentha piperita L. (peppermint), Melissa officinalis L. (lemon balm) and Cordia verbenacea DC (black sage) to adults of the generalist lacewing predator Ceraeochrysa cubana Hagen (Neuroptera: Chrysopidae). This predator is commonly found in agroecosystems in Brazil and it feeds on aphids, mites, small caterpillars, insect eggs and scales. We further tested the effect of these plant species on the survival, development and oviposition of C. cubana. Finally, we evaluated the survival of larvae and adults of C. cubana when only flowers of basil were offered. Females of C. cubana were attracted to basil but not to the remaining aromatic plants. Larvae survival was higher when individuals had access only to basil leaf than when they had access to peppermint, lemon balm, black sage or water. Adult survival on leaf treatments and on water was no longer than three days. Flowers of basil enhanced predator larvae survival, yet they did not reach adulthood. Adults fed on basil flowers lived longer compared with water, but they did not reproduce. Basil is a promising aromatic plant species to be considered for conservation biological control programs. Besides being attractive to adults of the generalist predator, it benefits larvae and adults by providing nutritional resources when prey or other resources are absent. Financial support: CNPq, FAPEMIG and CAPES (Brazil).

Keywords: basil, chrysopidae, conservation biological control, companion plants

Procedia PDF Downloads 257
12229 Assessment of Hypersaline Outfalls via Computational Fluid Dynamics Simulations: A Case Study of the Gold Coast Desalination Plant Offshore Multiport Brine Diffuser

Authors: Mitchell J. Baum, Badin Gibbes, Greg Collecutt

Abstract:

This study details a three-dimensional field-scale numerical investigation conducted for the Gold Coast Desalination Plant (GCDP) offshore multiport brine diffuser. Quantitative assessment of diffuser performance with regard to trajectory, dilution and mapping of seafloor concentration distributions was conducted for 100% plant operation. The quasi-steady Computational Fluid Dynamics (CFD) simulations were performed using the Reynolds averaged Navier-Stokes equations with a k-ω shear stress transport turbulence closure scheme. The study compliments a field investigation, which measured brine plume characteristics under similar conditions. CFD models used an iterative mesh in a domain with dimensions 400 m long, 200 m wide and an average depth of 24.2 m. Acoustic Doppler current profiler measurements conducted in the companion field study exhibited considerable variability over the water column. The effect of this vertical variability on simulated discharge outcomes was examined. Seafloor slope was also accommodated into the model. Ambient currents varied predominantly in the longshore direction – perpendicular to the diffuser structure. Under these conditions, the alternating port orientation of the GCDP diffuser resulted in simultaneous subjection to co-propagating and counter-propagating ambient regimes. Results from quiescent ambient simulations suggest broad agreement with empirical scaling arguments traditionally employed in design and regulatory assessments. Simulated dynamic ambient regimes showed the influence of ambient crossflow upon jet trajectory, dilution and seafloor concentration is significant. The effect of ambient flow structure and the subsequent influence on jet dynamics is discussed, along with the implications for using these different simulation approaches to inform regulatory decisions.

Keywords: computational fluid dynamics, desalination, field-scale simulation, multiport brine diffuser, negatively buoyant jet

Procedia PDF Downloads 214
12228 Effects of Bulblet Induction Medium on Bulb Size and Weight of Endemic Fritillaria aurea Schoot after Treatment with Putrescine for Different Durations of Time

Authors: Suleyman Kizil, Khalid Mahmood Khavar

Abstract:

Fritillaria aurea Schott is an important horticultural crop with high economic potential for the ornamental plant industry and is endemic to the Central and South-Eastern Anatolian regions of Türkiye. This study reports an experiment conducted under in vitro conditions to improve the weight and diameter of the in vitro regenerated bulblets. The micro bulblets used in this study were obtained from callus induced on half-sliced bulblets cultured on MS medium containing 0.1 mg L⁻¹ NAA + 0.05 TDZ (R₁ medium) and 0.1 mg L⁻¹ NAA + 0.10 mg L⁻¹ TDZ (R₂ medium). Thereafter, the micro bulblets obtained from here were treated with 50 mg L⁻¹ putrescine, (tetramethylenediamine) for 3, 5, and 7 weeks. The putrescine treatment has a significant effect on the increase in diameter and weight of bulblets when compared to initial diameters, irrespective of the treatment periods and seed germination medium. When the duration of putrescine in weeks was compared, 7 weeks of treatments with putrescine were more conducive for induction in bulblet weight compared to 3 and 5 weeks treatment periods. Maximum seed weight of 0.52 grams was noted on 7 weeks of putrescine treated bulblets regenerated on 0.1 mg L⁻¹ TDZ. This strategy to increase bulb weight and diameter could be positively used to conserve and multiply this beautiful ornamental and endemic plant species.

Keywords: Fritillaria aurea, bulblet, diameter, weight, micropropagation, polyamine

Procedia PDF Downloads 25
12227 Application of Monitoring of Power Generation through GPRS Network in Rural Residênias Cabo Frio/Rj

Authors: Robson C. Santos, David D. Oliveira, Matheus M. Reis, Gerson G. Cunha, Marcos A. C. Moreira

Abstract:

The project demonstrates the construction of a solar power generation, integrated inverter equipment to a "Grid-Tie" by converting direct current generated by solar panels, into alternating current, the same parameters of frequency and voltage concessionaire distribution network. The energy generated is quantified by smart metering module that transmits the information in specified periods of time to a microcontroller via GSM modem. The modem provides the measured data on the internet, using networks and cellular antennas. The monitoring, fault detection and maintenance are performed by a supervisory station. Employed board types, best inverter selection and studies about control equipment and devices have been described. The article covers and explores the global trend of implementing smart distribution electrical energy networks and the incentive to use solar renewable energy. There is the possibility of the excess energy produced by the system be purchased by the local power utility. This project was implemented in residences in the rural community of the municipality of Cabo Frio/RJ. Data could be seen through daily measurements during the month of November 2013.

Keywords: rural residence, supervisory, smart grid, solar energy

Procedia PDF Downloads 593
12226 Application of Imperialist Competitive Algorithm for Optimal Location and Sizing of Static Compensator Considering Voltage Profile

Authors: Vahid Rashtchi, Ashkan Pirooz

Abstract:

This paper applies the Imperialist Competitive Algorithm (ICA) to find the optimal place and size of Static Compensator (STATCOM) in power systems. The output of the algorithm is a two dimensional array which indicates the best bus number and STATCOM's optimal size that minimizes all bus voltage deviations from their nominal value. Simulations are performed on IEEE 5, 14, and 30 bus test systems. Also some comparisons have been done between ICA and the famous Particle Swarm Optimization (PSO) algorithm. Results show that how this method can be considered as one of the most precise evolutionary methods for the use of optimum compensator placement in electrical grids.

Keywords: evolutionary computation, imperialist competitive algorithm, power systems compensation, static compensators, voltage profile

Procedia PDF Downloads 605
12225 Iron Oxide Reduction Using Solar Concentration and Carbon-Free Reducers

Authors: Bastien Sanglard, Simon Cayez, Guillaume Viau, Thomas Blon, Julian Carrey, Sébastien Lachaize

Abstract:

The need to develop clean production processes is a key challenge of any industry. Steel and iron industries are particularly concerned since they emit 6.8% of global anthropogenic greenhouse gas emissions. One key step of the process is the high-temperature reduction of iron ore using coke, leading to large amounts of CO2 emissions. One route to decrease impacts is to get rid of fossil fuels by changing both the heat source and the reducer. The present work aims at investigating experimentally the possibility to use concentrated solar energy and carbon-free reducing agents. Two sets of experimentations were realized. First, in situ X-ray diffraction on pure and industrial powder of hematite was realized to study the phase evolution as a function of temperature during reduction under hydrogen and ammonia. Secondly, experiments were performed on industrial iron ore pellets, which were reduced by NH3 or H2 into a “solar furnace” composed of a controllable 1600W Xenon lamp to simulate and control the solar concentrated irradiation of a glass reactor and of a diaphragm to control light flux. Temperature and pressure were recorded during each experiment via thermocouples and pressure sensors. The percentage of iron oxide converted to iron (called thereafter “reduction ratio”) was found through Rietveld refinement. The power of the light source and the reduction time were varied. Results obtained in the diffractometer reaction chamber show that iron begins to form at 300°C with pure Fe2O3 powder and 400°C with industrial iron ore when maintained at this temperature for 60 minutes and 80 minutes, respectively. Magnetite and wuestite are detected on both powders during the reduction under hydrogen; under ammonia, iron nitride is also detected for temperatures between400°C and 600°C. All the iron oxide was converted to iron for a reaction of 60 min at 500°C, whereas a conversion ratio of 96% was reached with industrial powder for a reaction of 240 min at 600°C under hydrogen. Under ammonia, full conversion was also reached after 240 min of reduction at 600 °C. For experimentations into the solar furnace with iron ore pellets, the lamp power and the shutter opening were varied. An 83.2% conversion ratio was obtained with a light power of 67 W/cm2 without turning over the pellets. Nevertheless, under the same conditions, turning over the pellets in the middle of the experiment permits to reach a conversion ratio of 86.4%. A reduction ratio of 95% was reached with an exposure of 16 min by turning over pellets at half time with a flux of 169W/cm2. Similar or slightly better results were obtained under an ammonia reducing atmosphere. Under the same flux, the highest reduction yield of 97.3% was obtained under ammonia after 28 minutes of exposure. The chemical reaction itself, including the solar heat source, does not produce any greenhouse gases, so solar metallurgy represents a serious way to reduce greenhouse gas emission of metallurgy industry. Nevertheless, the ecological impact of the reducers must be investigated, which will be done in future work.

Keywords: solar concentration, metallurgy, ammonia, hydrogen, sustainability

Procedia PDF Downloads 138
12224 Modeling the Downstream Impacts of River Regulation on the Grand Lake Meadows Complex using Delft3D FM Suite

Authors: Jaime Leavitt, Katy Haralampides

Abstract:

Numerical modelling has been used to investigate the long-term impact of a large dam on downstream wetland areas, specifically in terms of changing sediment dynamics in the system. The Mactaquac Generating Station (MQGS) is a 672MW run-of-the-river hydroelectric facility, commissioned in 1968 on the mainstem of the Wolastoq|Saint John River in New Brunswick, Canada. New Brunswick Power owns and operates the dam and has been working closely with the Canadian Rivers Institute at UNB Fredericton on a multi-year, multi-disciplinary project investigating the impact the dam has on its surrounding environment. With focus on the downstream river, this research discusses the initialization, set-up, calibration, and preliminary results of a 2-D hydrodynamic model using the Delft3d Flexible Mesh Suite (successor of the Delft3d 4 Suite). The flexible mesh allows the model grid to be structured in the main channel and unstructured in the floodplains and other downstream regions with complex geometry. The combination of grid types improves computational time and output. As the movement of water governs the movement of sediment, the calibrated and validated hydrodynamic model was applied to sediment transport simulations, particularly of the fine suspended sediments. Several provincially significant Protected Natural Areas and federally significant National Wildlife Areas are located 60km downstream of the MQGS. These broad, low-lying floodplains and wetlands are known as the Grand Lake Meadows Complex (GLM Complex). There is added pressure to investigate the impacts of river regulation on these protected regions that rely heavily on natural river processes like sediment transport and flooding. It is hypothesized that the fine suspended sediment would naturally travel to the floodplains for nutrient deposition and replenishment, particularly during the freshet and large storms. The purpose of this research is to investigate the impacts of river regulation on downstream environments and use the model as a tool for informed decision making to protect and maintain biologically productive wetlands and floodplains.

Keywords: hydrodynamic modelling, national wildlife area, protected natural area, sediment transport.

Procedia PDF Downloads 6
12223 The Effect of Santolina Plant Extract on Nitro-Oxidative Stress

Authors: Sabrina Sebbane, Alina Elena Parvu

Abstract:

Introduction: Santolina rosmarinifolia is a plant of the Santolina genus, a family made of medicinal plants widely used. Some of the Santolina species have been proven to have potent anti-inflammatory and anti-oxidant effects. However, no in vivo study has been made to demonstrate this in Santolina rosmarinifolia. The aim of our study is to experimentally evaluate the potential anti-inflammatory and anti-oxidant effects of Santolina rosmarinifolia plant extracts on acute inflammation in rats. These effects are defined by measuring the modifications on nitric oxide, reactive oxygen species and anti-oxidant response in serum. Materials and Methods: Rats were divided into 5 groups (n=6). Three groups were given Santolina rosmarinifolia extract by gavage in different concentrations(100%, 50%, 25%) for a week. Inflammation was induced by i.m injection of turpentine oil on the 8th day. One group was only given turpentine oil and the fifth group acted as control and was given only saline solution. Blood was collected and serum separated. Global tests were used to measure the oxidative stress, total oxidative status (TOS), total antioxidant reactivity (TAR) and the modified method of Griess assay to measure NO synthesis. Malondilaldehyde (MDA) and thiols levels were also assessed. Results: Santolina rosmarinifolia did not significantly change the TOS levels (p > 0.05). Santolina rosmarinifolia 25% and 50% decreased significantly the TAR levels (p < 0.001). Santolina 100% didn't have a significant effect on TAR (p > 0.05). All concentrations of Santolina rosmarinifolia increased the oxidative stress index (OSI) significantly(p < 0.05). Santolina rosmarinifolia 100% significantly decreased NO synthesis (p value < 0.05). In the diluted Santolina groups, no significant effect on NO synthesis was observed. In the groups treated with Santolina 100% and Santolina rosmarinifolia 50%, thiols concentration were significantly higher compared to the inflammation group (p < 0.02). A higher stimulatory effect was found in the Santolina 25% group (p value < 0.05). MDA levels were not significantly modified by the administration of Santolina rosmarinifolia (p > 0.05). Conclusion: All three solutions of Santolina rosmarinifolia had no important effect on oxidant production. However, Santolina rosmarinifolia solutions had a positive effect by increasing the thiols concentration in the serum of the models. The sum of all the effects produced by the administration of Santolina did not show a significant decrease of nitro-oxidative stress. Further experiments including smaller concentrations of Santolina rosmarinifolia will be made. Santolina rosmarinifolia should also be tested as a curative treatment.

Keywords: inflammation, MDA, nitric oxide, santolina rosmarinifolia, thiols, TAR, TOS

Procedia PDF Downloads 260
12222 Modelling and Simulation of Cascaded H-Bridge Multilevel Single Source Inverter Using PSIM

Authors: Gaddafi Sani Shehu, Tankut Yalcınoz, Abdullahi Bala Kunya

Abstract:

Multilevel inverters such as flying capacitor, diode-clamped, and cascaded H-bridge inverters are very popular particularly in medium and high power applications. This paper focuses on a cascaded H-bridge module using a single direct current (DC) source in order to generate an 11-level output voltage. The noble approach reduces the number of switches and gate drivers, in comparison with a conventional method. The anticipated topology produces more accurate result with an isolation transformer at high switching frequency. Different modulation techniques can be used for the multilevel inverter, but this work features modulation techniques known as selective harmonic elimination (SHE).This modulation approach reduces the number of carriers with reduction in Switching Losses, Total Harmonic Distortion (THD), and thereby increasing Power Quality (PQ). Based on the simulation result obtained, it appears SHE has the ability to eliminate selected harmonics by chopping off the fundamental output component. The performance evaluation of the proposed cascaded multilevel inverter is performed using PSIM simulation package and THD of 0.94% is obtained.

Keywords: cascaded H-bridge multilevel inverter, power quality, selective harmonic elimination

Procedia PDF Downloads 419
12221 Improving Fingerprinting-Based Localization (FPL) System Using Generative Artificial Intelligence (GAI)

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 47
12220 Machine Learning-Based Techniques for Detecting and Mitigating Cyber-attacks on Automatic Generation Control in Smart Grids

Authors: Sami M. Alshareef

Abstract:

The rapid growth of smart grid technology has brought significant advancements to the power industry. However, with the increasing interconnectivity and reliance on information and communication technologies, smart grids have become vulnerable to cyber-attacks, posing significant threats to the reliable operation of power systems. Among the critical components of smart grids, the Automatic Generation Control (AGC) system plays a vital role in maintaining the balance between generation and load demand. Therefore, protecting the AGC system from cyber threats is of paramount importance to maintain grid stability and prevent disruptions. Traditional security measures often fall short in addressing sophisticated and evolving cyber threats, necessitating the exploration of innovative approaches. Machine learning, with its ability to analyze vast amounts of data and learn patterns, has emerged as a promising solution to enhance AGC system security. Therefore, this research proposal aims to address the challenges associated with detecting and mitigating cyber-attacks on AGC in smart grids by leveraging machine learning techniques on automatic generation control of two-area power systems. By utilizing historical data, the proposed system will learn the normal behavior patterns of AGC and identify deviations caused by cyber-attacks. Once an attack is detected, appropriate mitigation strategies will be employed to safeguard the AGC system. The outcomes of this research will provide power system operators and administrators with valuable insights into the vulnerabilities of AGC systems in smart grids and offer practical solutions to enhance their cyber resilience.

Keywords: machine learning, cyber-attacks, automatic generation control, smart grid

Procedia PDF Downloads 85
12219 Effect of In-Season Linear Sprint Training on Sprint Kinematics of Amateur Soccer Players

Authors: Avinash Kharel

Abstract:

Background: - Linear sprint training is one possible approach to developing sprint performance, a crucial skill to focus on in soccer. Numerous methods, including various on-field training options, can be employed to attain this goal. However, the effect of In-season linear sprint training on sprint performance and related kinetics changes are unknown in a professional setting. The study aimed to investigate the effect of in-season linear sprint training on the sprint kinematics of amateur soccer players. Methods: - After familiarization, a 4-week training protocol was completed with sprint performance and Force Velocity (FV) profiles was compared before and after the training. Eighteen amateur soccer male players (Age 22 ± 2 years: Height: 178 ± 7cm; body-mass: 74 ± 8 Kg, 30-m split-time: 4.398 ± s) participated in the study. Sprint kinematics variables, including maximum Sprint Velocity (V0), Theoretical Maximum Force (F0), Maximum Force Output per kilogram of body weight (N/KG), Maximum Velocity (V(0)), Maximum Power Output (P MAX (W)), Ratio of Force to Velocity (FV), and Ratio of Force to Velocity at Peak power were measured. Results: - Results showed significant improvements in Maximum Sprint Velocity (p<0.01, ES=0.89), Theoretical Maximum Force (p<0.05, ES=0.50), Maximum Force Output per kilogram of body weight (p<0.05, ES=0.42), Maximum Power Output (p<0.05, ES=0.52), and Ratio of Force to Velocity at Peak Power (RF PEAK) (p<0.05, ES=0.44) post-training. There were no significant changes in the ratio of Force to Velocity (FV) and Maximum Velocity V (0) post-training (p>0.05). Conclusion: - These findings suggest that In-season linear sprint training can effectively improve certain sprint kinematics variables in amateur soccer players. Coaches and players should consider incorporating linear sprint training into their in-season training programs to improve sprint performance.

Keywords: sprint performance, training intervention, soccer, kinematics

Procedia PDF Downloads 73
12218 Designing of Nano-materials for Waste Heat Conversion into Electrical Energy Thermoelectric generator

Authors: Wiqar Hussain Shah

Abstract:

The electrical and thermal properties of the doped Tellurium Telluride (Tl10Te6) chalcogenide nano-particles are mainly characterized by a competition between metallic (hole doped concentration) and semi-conducting state. We have studied the effects of Sn doping on the electrical and thermoelectric properties of Tl10-xSnxTe6 (1.00 ≤x≤ 2.00), nano-particles, prepared by solid state reactions in sealed silica tubes and ball milling method. Structurally, all these compounds were found to be phase pure as confirmed by the x-rays diffractometery (XRD) and energy dispersive X-ray spectroscopy (EDS) analysis. Additionally crystal structure data were used to model the data and support the findings. The particles size was calculated from the XRD data by Scherrer’s formula. The EDS was used for an elemental analysis of the sample and declares the percentage of elements present in the system. The thermo-power or Seebeck co-efficient (S) was measured for all these compounds which show that S increases with increasing temperature from 295 to 550 K. The Seebeck coefficient is positive for the whole temperature range, showing p-type semiconductor characteristics. The electrical conductivity was investigated by four probe resistivity techniques revealed that the electrical conductivity decreases with increasing temperature, and also simultaneously with increasing Sn concentration. While for Seebeck coefficient the trend is opposite which is increases with increasing temperature. These increasing behavior of Seebeck coefficient leads to high power factor which are increases with increasing temperature and Sn concentration except For Tl8Sn2Te6 because of lowest electrical conductivity but its power factor increases well with increasing temperature.

Keywords: Sn doping in Tellurium Telluride nano-materials, electron holes competition, Seebeck co-efficient, effects of Sn doping on Electrical conductivity, effects on Power factor

Procedia PDF Downloads 44