Search results for: artificial neural networks; crop water stress index; canopy temperature
22418 Regression of Hand Kinematics from Surface Electromyography Data Using an Long Short-Term Memory-Transformer Model
Authors: Anita Sadat Sadati Rostami, Reza Almasi Ghaleh
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Surface electromyography (sEMG) offers important insights into muscle activation and has applications in fields including rehabilitation and human-computer interaction. The purpose of this work is to predict the degree of activation of two joints in the index finger using an LSTM-Transformer architecture trained on sEMG data from the Ninapro DB8 dataset. We apply advanced preprocessing techniques, such as multi-band filtering and customizable rectification methods, to enhance the encoding of sEMG data into features that are beneficial for regression tasks. The processed data is converted into spike patterns and simulated using Leaky Integrate-and-Fire (LIF) neuron models, allowing for neuromorphic-inspired processing. Our findings demonstrate that adjusting filtering parameters and neuron dynamics and employing the LSTM-Transformer model improves joint angle prediction performance. This study contributes to the ongoing development of deep learning frameworks for sEMG analysis, which could lead to improvements in motor control systems.Keywords: surface electromyography, LSTM-transformer, spiking neural networks, hand kinematics, leaky integrate-and-fire neuron, band-pass filtering, muscle activity decoding
Procedia PDF Downloads 1122417 Large Core Silica Few-Mode Optical Fibers with Reduced Differential Mode Delay and Enhanced Mode Effective Area over 'C'-Band
Authors: Anton V. Bourdine, Vladimir A. Burdin, Oleg R. Delmukhametov
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This work presents a fast and simple method for the design of large core silica optical fibers with differential mode delay (DMD) management. Some results are reported concerned with refractive index profile optimization for 42 µm core 16-LP-mode optical fiber for next-generation optical networks. Here special refractive index profile form provides total DMD reducing over all mode staff under desired enhanced mode effective area. Method for the simulation of 'real manufactured' few-mode optical fiber (FMF) core geometry differing from the desired optimized structure by core non-symmetrical ellipticity and refractive index profile deviation including local fluctuations is proposed. Results of the following analysis of optimized FMF with inserted geometry distortions performed by earlier on developed modification of rigorous mixed finite-element method showed strong DMD degradation that requires additional higher-order mode management. In addition, this work also presents a method for design mode division multiplexer channel precision spatial positioning scheme at FMF core end that provides one of the potentiality solutions of described DMD degradation problem concerned with 'distorted' core geometry due to features of optical fiber manufacturing techniques.Keywords: differential mode delay, few-mode optical fibers, nonlinear Shannon limit, optical fiber non-circularity, ‘real manufactured’ optical fiber core geometry simulation, refractive index profile optimization
Procedia PDF Downloads 15722416 Preliminary Study of Hand Gesture Classification in Upper-Limb Prosthetics Using Machine Learning with EMG Signals
Authors: Linghui Meng, James Atlas, Deborah Munro
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There is an increasing demand for prosthetics capable of mimicking natural limb movements and hand gestures, but precise movement control of prosthetics using only electrode signals continues to be challenging. This study considers the implementation of machine learning as a means of improving accuracy and presents an initial investigation into hand gesture recognition using models based on electromyographic (EMG) signals. EMG signals, which capture muscle activity, are used as inputs to machine learning algorithms to improve prosthetic control accuracy, functionality and adaptivity. Using logistic regression, a machine learning classifier, this study evaluates the accuracy of classifying two hand gestures from the publicly available Ninapro dataset using two-time series feature extraction algorithms: Time Series Feature Extraction (TSFE) and Convolutional Neural Networks (CNNs). Trials were conducted using varying numbers of EMG channels from one to eight to determine the impact of channel quantity on classification accuracy. The results suggest that although both algorithms can successfully distinguish between hand gesture EMG signals, CNNs outperform TSFE in extracting useful information for both accuracy and computational efficiency. In addition, although more channels of EMG signals provide more useful information, they also require more complex and computationally intensive feature extractors and consequently do not perform as well as lower numbers of channels. The findings also underscore the potential of machine learning techniques in developing more effective and adaptive prosthetic control systems.Keywords: EMG, machine learning, prosthetic control, electromyographic prosthetics, hand gesture classification, CNN, computational neural networks, TSFE, time series feature extraction, channel count, logistic regression, ninapro, classifiers
Procedia PDF Downloads 3122415 Rooftop Rainwater Harvesting for Sustainable Organic Farming: Insights from Smart cities in India
Authors: Rajkumar Ghosh
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India faces a critical task of water shortage, specifically during dry seasons, which adversely impacts agricultural productivity and food protection. Natural farming, specializing in sustainable practices, demands green water management in smart cities in India. This paper examines how rooftop rainwater harvesting (RRWH) can alleviate water scarcity and support sustainable organic farming practices in India. RRWH emerges as a promising way to increase water availability for the duration of dry intervals and decrease reliance on traditional water sources in smart cities. The look at explores the capacity of RRWH to enhance water use performance, help crop growth, enhance soil health, and promote ecological stability inside the farming ecosystem. The medical paper delves into the advantages, challenges, and implementation techniques of RRWH in organic farming. It addresses demanding situations, including seasonal variability of rainfall, limited rooftop vicinity, and monetary concerns. Moreover, it analyses broader environmental and socio-economic implications of RRWH for sustainable agriculture, emphasizing water conservation, biodiversity protection, and the social properly-being of farming communities. The belief underscores the importance of RRWH as a sustainable solution for reaching the aim of sustainable agriculture in natural farming in India. It emphasizes the want for further studies, policy advocacy, and capacity-building initiatives to promote RRWH adoption and assist the transformation in the direction of sustainable organic farming systems. The paper proposes adaptive strategies to triumph over demanding situations and optimize the advantages of RRWH in organic farming. By way of doing so, India can make vast development in addressing water scarcity issues and making sure a greater resilient and sustainable agricultural future in smart cities.Keywords: rooftop rainwater harvesting, organic farming, green water management, food protection, ecological stabilty
Procedia PDF Downloads 10322414 Development of Vacuum Planar Membrane Dehumidifier for Air-Conditioning
Authors: Chun-Han Li, Tien-Fu Yang, Chen-Yu Chen, Wei-Mon Yan
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The conventional dehumidification method in air-conditioning system mostly utilizes a cooling coil to remove the moisture in the air via cooling the supply air down below its dew point temperature. During the process, it needs to reheat the supply air to meet the set indoor condition that consumes a considerable amount of energy and affect the coefficient of performance of the system. If the processes of dehumidification and cooling are separated and operated respectively, the indoor conditions will be more efficiently controlled. Therefore, decoupling the dehumidification and cooling processes in heating, ventilation and air conditioning system is one of the key technologies as membrane dehumidification processes for the next generation. The membrane dehumidification method has the advantages of low cost, low energy consumption, etc. It utilizes the pore size and hydrophilicity of the membrane to transfer water vapor by mass transfer effect. The moisture in the supply air is removed by the potential energy and driving force across the membrane. The process can save the latent load used to condense water, which makes more efficient energy use because it does not involve heat transfer effect. In this work, the performance measurements including the permeability and selectivity of water vapor and air with the composite and commercial membranes were conducted. According to measured data, we can choose the suitable dehumidification membrane for designing the flow channel length and components of the planar dehumidifier. The vacuum membrane dehumidification system was set up to examine the effects of temperature, humidity, vacuum pressure, flow rate, the coefficient of performance and other parameters on the dehumidification efficiency. The results showed that the commercial Nafion membrane has better water vapor permeability and selectivity. They are suitable for filtration with water vapor and air. Meanwhile, Nafion membrane has promising potential in the dehumidification process.Keywords: vacuum membrane dehumidification, planar membrane dehumidifier, water vapour and air permeability, air conditioning
Procedia PDF Downloads 14722413 Research on Resilience-Oriented Disintegration in System-of-System
Authors: Hang Yang, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge
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The system-of-systems (SoS) are utilized to characterize networks formed by integrating individual complex systems that demonstrate interdependence and interconnectedness. Research on the disintegration issue in SoS is significant in improving network survivability, maintaining network security, and optimizing SoS architecture. Accordingly, this study proposes an integrated framework called resilience-oriented disintegration in SoS (SoSRD), for modeling and solving the issue of SoS disintegration. Firstly, a SoS disintegration index (SoSDI) is presented to evaluate the disintegration effect of SoS. This index provides a practical description of the disintegration process and is the first integration of the network disintegration model and resilience models. Subsequently, we propose a resilience-oriented disintegration method based on reinforcement learning (RDRL) to enhance the efficiency of SoS disintegration. This method is not restricted by the problem scenario as well as considering the coexistence of disintegration (node/link removal) and recovery (node/link addition) during the process of SoS disintegration. Finally, the effectiveness and superiority of the proposed SoSRD are demonstrated through a case study. We demonstrate that our proposed framework outperforms existing indexes and methods in both node and link disintegration scenarios, providing a fresh perspective on network disintegration. The findings provide crucial insights into dismantling harmful SoS and designing a more resilient SoS.Keywords: system-of-systems, disintegration index, resilience, reinforcement learning
Procedia PDF Downloads 1622412 Performance of Growing Rahaji Bulls Fed Diets Containing Similar Concentrates and Different Crop Residues in a Semi-Arid Environment
Authors: Husaini Sama
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The study was conducted, in a 120 - day’s trial, to monitor the performance of growing Rahaji bulls fed different crop residues. There were four experimental treatments, each containing three (3) bull-calves. The first three (experimental) diets were prepared with rice straw, millet stalks and a combination of the two in equal proportions. These 3 diets were supplemented with concentrates. Treatments 1, 2 and 3 consisted of rice straw, millet stalk and combination of rice straw and millet stalk in equal ratio, respectively as basal feeds, while, Treatment 4 (containing standard diet of cow pea haulms, rice straw and wheat offal) served as control to compare with the other treatments. Data on feed intake and livability was collected on daily basis and that of live weight gain and feed conversion ratio were collected fortnightly, but data on apparent nutrient retention trial was collected towards the end of the experiment. Water was offered ad libitum. Records obtained were subjected to statistical analysis using SPSS (1988) software package in accordance with a Completely Randomized Design (CRD). Results obtained indicated that feed intake was significantly higher (P<0.05) for calves on treatments 3 and 4 compared to those on treatments 1and 2. The study observed that it was cheaper to formulate diets 2 and 3 than the other 2 diets. The control diet (T4) was observed to be relatively more expensive than the other 3 formulated diets. It was concluded from the findings that, concentrate containing combination of rice straw and cereal stalks was economical and satisfactory for feeding growing Rahaji bulls in this ecological zone (Semi-arid environment).Keywords: rahaji bulls, crop residues, concentrates, semi-arid environment
Procedia PDF Downloads 18722411 A Study of Stress and Coping Strategies of School Teachers
Authors: G.S. Patel
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In this research paper the discussion have been made on teachers work mental stress and coping strategies. Stress Measurement scale was developed for school teachers. All the scientific steps of test construction was followed. For this test construction, different factors like teachers workplace, teachers' residential area, teachers' family life, teachers' ability and skills, economic factors and other factors to construct teachers stress measurement scale. In this research tool, situational statements have been made and teachers have to give a response in each statement on five-point rating scale what they experienced in their daily life. Special features of the test also established like validity and reliability of this test and also computed norms for its interpretation. A sample of 320 teachers of school teachers of Gujarat state was selected by Cluster sampling technique. t-test was computed for testing null hypothesis. The main findings of the present study are Urban area teachers feel more stressful situation compare to rural area teachers. Those teachers who live in the joint family feel less stress compare to teachers who live in a nuclear family. This research work is very useful to prepare list of activities to reduce teachers mental stress.Keywords: stress measurement scale, level of stress, validity, reliability, norms
Procedia PDF Downloads 19522410 Meaning in Life, Hope, and Mental Health: Relation between Meaning in Life, Hope, Depression, Anxiety, and Stress among Afghan Refugees in Iran
Authors: Mustafa Jahanara
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The present research was carried out in order to investigate the relationship between meaning in life and hope with depression, anxiety and stress in Afghan Refugees in Alborz province in Iran. In this research, method of study is a descriptive correlation type. One hundred and fifty-eight Afghan refugees (64 male, 94 female) participated in this study. All participants completed the Meaning in Life Questionnaires (MLQ), Hope Scale (HS), and The Depression Anxiety Stress Scales (DASS-21). The results revealed that Meaning in Life was positively associated with hope, presence of meaning, search of meaning, and negatively associated with depression and anxiety. Hope was positively associated with presence of meaning and search of meaning, and hope was negatively associated with depression, anxiety, and stress. Depression, anxiety, and stress were positively correlated with each other. Meaning in life and hope could influence on mental health.Keywords: Afghan refugees, meaning of life, hope, depression, anxiety and stress
Procedia PDF Downloads 41622409 Optimization of Surface Roughness in Additive Manufacturing Processes via Taguchi Methodology
Authors: Anjian Chen, Joseph C. Chen
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This paper studies a case where the targeted surface roughness of fused deposition modeling (FDM) additive manufacturing process is improved. The process is designing to reduce or eliminate the defects and improve the process capability index Cp and Cpk for an FDM additive manufacturing process. The baseline Cp is 0.274 and Cpk is 0.654. This research utilizes the Taguchi methodology, to eliminate defects and improve the process. The Taguchi method is used to optimize the additive manufacturing process and printing parameters that affect the targeted surface roughness of FDM additive manufacturing. The Taguchi L9 orthogonal array is used to organize the parameters' (four controllable parameters and one non-controllable parameter) effectiveness on the FDM additive manufacturing process. The four controllable parameters are nozzle temperature [°C], layer thickness [mm], nozzle speed [mm/s], and extruder speed [%]. The non-controllable parameter is the environmental temperature [°C]. After the optimization of the parameters, a confirmation print was printed to prove that the results can reduce the amount of defects and improve the process capability index Cp from 0.274 to 1.605 and the Cpk from 0.654 to 1.233 for the FDM additive manufacturing process. The final results confirmed that the Taguchi methodology is sufficient to improve the surface roughness of FDM additive manufacturing process.Keywords: additive manufacturing, fused deposition modeling, surface roughness, six-sigma, Taguchi method, 3D printing
Procedia PDF Downloads 39322408 Soil Stress State under Tractive Tire and Compaction Model
Authors: Prathuang Usaborisut, Dithaporn Thungsotanon
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Soil compaction induced by a tractor towing trailer becomes a major problem associated to sugarcane productivity. Soil beneath the tractor’s tire is not only under compressing stress but also shearing stress. Therefore, in order to help to understand such effects on soil, this research aimed to determine stress state in soil and predict compaction of soil under a tractive tire. The octahedral stress ratios under the tires were higher than one and much higher under higher draft forces. Moreover, the ratio was increasing with increase of number of tire’s passage. Soil compaction model was developed using data acquired from triaxial tests. The model was then used to predict soil bulk density under tractive tire. The maximum error was about 4% at 15 cm depth under lower draft force and tended to increase with depth and draft force. At depth of 30 cm and under higher draft force, the maximum error was about 16%.Keywords: draft force, soil compaction model, stress state, tractive tire
Procedia PDF Downloads 35222407 Investigation of Irrigation Water Quality at Al-Wafra Agricultural Area, Kuwait
Authors: Mosab Aljeri, Ali Abdulraheem
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The water quality of five water types at Al-Wuhaib farm, Al-Wafra area, was studies through onsite field measurements, including pH, temperature, electrical conductivity (EC), and dissolved oxygen (DO), for four different water types. Biweekly samples were collected and analyzed for two months to obtain data of chemicals, nutrients, organics, and heavy metals. The field and laboratory results were compared with irrigation standards of Kuwait Environmental Public Authority (KEPA). The pH values of the five samples sites were within the maximum and minimum limits of KEPA standards. Based on EC values, two groups of water types were observed. The first group represents freshwater quality originated from freshwater Ministry of Electricity & Water & Renewable Energy (MEWRE) line or from freshwater tanks or treated wastewater. The second group represents brackish water type originated from groundwater or treated water mixed with groundwater. The study indicated that all nitrogen forms (ammonia, Total Kjeldahl nitrogen (TKN), Total nitrogen (TN)), total phosphate concentrations and all tested heavy metals for the five water types were below KEPA standards. These macro and micro nutrients are essential for plant growth and can be used as fertilizers. The study suggest that the groundwater should be treated and disinfected in the farming area. Also, these type of studies shall be carried out routinely to all farm areas to ensure safe water use and safe agricultural produce.Keywords: salinity, heavy metals, ammonia, phosphate
Procedia PDF Downloads 8722406 On Crack Tip Stress Field in Pseudo-Elastic Shape Memory Alloys
Authors: Gulcan Ozerim, Gunay Anlas
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In shape memory alloys, upon loading, stress increases around crack tip and a martensitic phase transformation occurs in early stages. In many studies the stress distribution in the vicinity of the crack tip is represented by using linear elastic fracture mechanics (LEFM) although the pseudo-elastic behavior results in a nonlinear stress-strain relation. In this study, the HRR singularity (Hutchinson, Rice and Rosengren), that uses Rice’s path independent J-integral, is tried to formulate the stress distribution around the crack tip. In HRR approach, the Ramberg-Osgood model for the stress-strain relation of power-law hardening materials is used to represent the elastic-plastic behavior. Although it is recoverable, the inelastic portion of the deformation in martensitic transformation (up to the end of transformation) resembles to that of plastic deformation. To determine the constants of the Ramberg-Osgood equation, the material’s response is simulated in ABAQUS using a UMAT based on ZM (Zaki-Moumni) thermo-mechanically coupled model, and the stress-strain curve of the material is plotted. An edge cracked shape memory alloy (Nitinol) plate is loaded quasi-statically under mode I and modeled using ABAQUS; the opening stress values ahead of the cracked tip are calculated. The stresses are also evaluated using the asymptotic equations of both LEFM and HRR. The results show that in the transformation zone around the crack tip, the stress values are much better represented when the HRR singularity is used although the J-integral does not show path independent behavior. For the nodes very close to the crack tip, the HRR singularity is not valid due to the non-proportional loading effect and high-stress values that go beyond the transformation finish stress.Keywords: crack, HRR singularity, shape memory alloys, stress distribution
Procedia PDF Downloads 32522405 Quality Assessment of New Zealand Mānuka Honeys Using Hyperspectral Imaging Combined with Deep 1D-Convolutional Neural Networks
Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer
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New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics
Procedia PDF Downloads 13922404 Neural Network Approaches for Sea Surface Height Predictability Using Sea Surface Temperature
Authors: Luther Ollier, Sylvie Thiria, Anastase Charantonis, Carlos E. Mejia, Michel Crépon
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Sea Surface Height Anomaly (SLA) is a signature of the sub-mesoscale dynamics of the upper ocean. Sea Surface Temperature (SST) is driven by these dynamics and can be used to improve the spatial interpolation of SLA fields. In this study, we focused on the temporal evolution of SLA fields. We explored the capacity of deep learning (DL) methods to predict short-term SLA fields using SST fields. We used simulated daily SLA and SST data from the Mercator Global Analysis and Forecasting System, with a resolution of (1/12)◦ in the North Atlantic Ocean (26.5-44.42◦N, -64.25–41.83◦E), covering the period from 1993 to 2019. Using a slightly modified image-to-image convolutional DL architecture, we demonstrated that SST is a relevant variable for controlling the SLA prediction. With a learning process inspired by the teaching-forcing method, we managed to improve the SLA forecast at five days by using the SST fields as additional information. We obtained predictions of a 12 cm (20 cm) error of SLA evolution for scales smaller than mesoscales and at time scales of 5 days (20 days), respectively. Moreover, the information provided by the SST allows us to limit the SLA error to 16 cm at 20 days when learning the trajectory.Keywords: deep-learning, altimetry, sea surface temperature, forecast
Procedia PDF Downloads 9022403 Impact Deformation and Fracture Behaviour of Cobalt-Based Haynes 188 Superalloy
Authors: Woei-Shyan Lee, Hao-Chien Kao
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The impact deformation and fracture behaviour of cobalt-based Haynes 188 superalloy are investigated by means of a split Hopkinson pressure bar. Impact tests are performed at strain rates ranging from 1×103 s-1 to 5×103 s-1 and temperatures between 25°C and 800°C. The experimental results indicate that the flow response and fracture characteristics of cobalt-based Haynes 188 superalloy are significantly dependent on the strain rate and temperature. The flow stress, work hardening rate and strain rate sensitivity all increase with increasing strain rate or decreasing temperature. It is shown that the impact response of the Haynes 188 specimens is adequately described by the Zerilli-Armstrong fcc model. The fracture analysis results indicate that the Haynes 188 specimens fail predominantly as the result of intensive localised shearing. Furthermore, it is shown that the flow localisation effect leads to the formation of adiabatic shear bands. The fracture surfaces of the deformed Haynes 188 specimens are characterised by dimple- and / or cleavage-like structure with knobby features. The knobby features are thought to be the result of a rise in the local temperature to a value greater than the melting point.Keywords: Haynes 188 alloy, impact, strain rate and temperature effect, adiabatic shearing
Procedia PDF Downloads 35922402 Assessment of Heavy Metals Contamination Levels in Groundwater: A Case Study of the Bafia Agricultural Area, Centre Region Cameroon
Authors: Carine Enow-Ayor Tarkang, Victorine Neh Akenji, Dmitri Rouwet, Jodephine Njdma, Andrew Ako Ako, Franco Tassi, Jules Remy Ngoupayou Ndam
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Groundwater is the major water resource in the whole of Bafia used for drinking, domestic, poultry and agricultural purposes, and being an area of intense agriculture, there is a great necessity to do a quality assessment. Bafia is one of the main food suppliers in the Centre region of Cameroon, and so to meet their demands, the farmers make use of fertilizers and other agrochemicals to increase their yield. Less than 20% of the population in Bafia has access to piped-borne water due to the national shortage, according to the authors best knowledge very limited studies have been carried out in the area to increase awareness of the groundwater resources. The aim of this study was to assess heavy metal contamination levels in ground and surface waters and to evaluate the effects of agricultural inputs on water quality in the Bafia area. 57 water samples (including 31 wells, 20 boreholes, 4 rivers and 2 springs) were analyzed for their physicochemical parameters, while collected samples were filtered, acidified with HNO3 and analyzed by ICP-MS for their heavy metal content (Fe, Ti, Sr, Al, Mn). Results showed that most of the water samples are acidic to slightly neutral and moderately mineralized. Ti concentration was significantly high in the area (mean value 130µg/L), suggesting another Ti source besides the natural input from Titanium oxides. The high amounts of Mn and Al in some cases also pointed to additional input, probably from fertilizers that are used in the farmlands. Most of the water samples were found to be significantly contaminated with heavy metals exceeding the WHO allowable limits (Ti-94.7%, Al-19.3%, Mn-14%, Fe-5.2% and Sr-3.5% above limits), especially around farmlands and topographic low areas. The heavy metal concentration was evaluated using the heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and degree of contamination (Cd), while the Ficklin diagram was used for the water based on changes in metal content and pH. The high mean values of HPI and Cd (741 and 5, respectively), which exceeded the critical limit, indicate that the water samples are highly contaminated, with intense pollution from Ti, Al and Mn. Based on the HPI and Cd, 93% and 35% of the samples, respectively, are unacceptable for drinking purposes. The lowest HPI value point also had the lowest EC (50 µS/cm), indicating lower mineralization and less anthropogenic influence. According to the Ficklin diagram, 89% of the samples fell within the near-neutral low-metal domain, while 9% fell in the near-neutral extreme-metal domain. Two significant factors were extracted from the PCA, explaining 70.6% of the total variance. The first factor revealed intense anthropogenic activity (especially from fertilizers), while the second factor revealed water-rock interactions. Agricultural activities thus have an impact on the heavy metal content of groundwater in the area; hence, much attention should be given to the affected areas in order to protect human health/life and thus sustainably manage this precious resource.Keywords: Bafia, contamination, degree of contamination, groundwater, heavy metal pollution index
Procedia PDF Downloads 8722401 Develop a Conceptual Data Model of Geotechnical Risk Assessment in Underground Coal Mining Using a Cloud-Based Machine Learning Platform
Authors: Reza Mohammadzadeh
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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.Keywords: data model, geotechnical risks, machine learning, underground coal mining
Procedia PDF Downloads 27422400 EHD Effect on the Dynamic Characteristics of a Journal Bearing Lubricated with Couple Stress Fluids
Authors: B. Chetti, W. A. Crosby
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This paper presents a numerical analysis for the dynamic performance of a finite journal bearing lubricated with couple stress fluid taking into account the effect of the deformation of the bearing liner. The modified Reynolds equation has been solved by using finite difference technique. The dynamic characteristics in terms of stiffness coefficients, damping coefficients, critical mass and whirl ratio are evaluated for different values of eccentricity ratio and elastic coefficient for a journal bearing lubricated with a couple stress fluids and a Newtonian fluid. The results show that the dynamic characteristics of journal bearings lubricated with couple stress fluids are improved compared to journal bearings lubricated with Newtonian fluids.Keywords: journal bearing, elastohydrodynamic, stability, couple stress
Procedia PDF Downloads 36322399 Studies on the Physico-Chemical Parameters of Jebba Lake, Niger State, Nigeria
Authors: M. B. Mshelia, J. K. Balogun, J. Auta, N. O. Bankole
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Studies on some aspects of the physico-chemical parameters of Jebba Lake, Niger State, Nigeria was carried out from January to December, 2011. The aim was to investigate some of the physico-chemical parameters relevant to life and health of fish in the water body. Six (6) sampling sites were selected at random which covered Northern (Faku and Awuru), middle (Old Gbajibo and Shankade) and southern zones (New Gbajibo and Jebba dam} of Jebba Lake. Sampling was carried out for the period of 12 Months. The Physico-chemical parameters that were considered were water temperature, pH, dissolved oxygen, electrical conductivity, water transparency, phosphate and nitrate. They were all measured using standard methods. The results showed that water temperature values ranged between 26.06 ± 0.15a in Jebba lake site to 27.34 ± 0.12b in Shankade sampling site, depth varied from 8.08m to 31.64m, water current was between 20.10.62 cm/sec and 26.46 cm/sec, Secchi disc transparency ranged from0.46±0.01 m in New Gbajibo, while the highest mean value was 0.53 ± 0.04 m in Jebba dam., pH varied from 6.49 ± 0.01 and 7.59,5.35±0.03a mg/l in New Gbajibo and 6.75 ± 0.03 mg/l in Faku.The dissolved oxygen varied between 5.35±0.03a mg/l in New Gbajibo and 6.75 ± 0.03 mg/l in Faku.,The mean conductivity value was highest in Faku and Jebba with 128.8 ± 0.32 and 128.8 ± 0.42homs/cm) respectively, Alkalinity ranged 43.00±0.02 to33.30±0.32 mg/l., The nitrate-nitrogen range (2.37 ± 0.08 – 6.40 ± 0.50mg/l)., The mean values of phosphate-phosphorus (PO4-P) recorded varied between 0.18 ± 0.00 mg/l in Faku to 0.47 + 0.10 mg/l in Old Gbajibo.The highest mean value for total dissolved solids was 57.88 ± 0.28 mg/l in Shankade, while the lowest mean value of 39.17 ± 0.42 mg/l was recorded in Faku. Free CO2 ranged from 1.75 mg/l to 2.94 mg/l, Biochemical oxygen demand (BOD) was between 4.25 mg/l and 5.41 mg/l and nitrate-nitrogen concentration was between 2.37 mg/l and 6.40 mg/l. There were significant differences (P < 0.05) between these parameters in relation to stations. Generally, the physico-chemical characteristics of Lake Jebba were within the productive values for aquatic systems, and strongly indicate that the lake is unpolluted.Keywords: Jebba Lake, water quality, secchi disc, DO meter, sampling sites, physico-chemical parameters
Procedia PDF Downloads 43622398 Correlation between General Intelligence, Emotional Intelligence and Stress Response after One Month Practice of Moderate Intensity Physical Exercise
Authors: Mohita Singh, Sunil Sachdev, Amrita Singh
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Background and Aim: Physical aerobic exercises promote positive changes in one’s mental health, intelligence, and ability to cope with stressful encounters. The present study was designed to explore the correlation between intelligence and stress parameters and to assess the correlation between the same parameters after the practice of one month of moderate-intensity physical exercise. Method: The study was conducted on thirty-five healthy male volunteer students to assess the correlation between stress parameters in subjects with varying level of general intelligence (GI) and emotional intelligence (EI). Correlation studies were again conducted after one month between the same parameters to evaluate the effect of moderate-intensity physical exercise (MIPE). Baseline values were recorded using standard scales. Result: IQ and EQ correlated negatively with both acute and chronic stress parameters and positively with each other. A positive correlation was found between acute and chronic stress. With the practice of one month of moderate-intensity physical exercise, there was significant increment between the parameters under study and hence improved results. Conclusion: MIPE improved correlation between GI, EI, stress parameters, and thus reduced stress and improved intelligence.Keywords: emotional intelligence, general intelligence, moderate intensity physical exercise, stress response
Procedia PDF Downloads 14522397 Root System Architecture Analysis of Sorghum Genotypes and Its Effect on Drought Adaptation
Authors: Hailemariam Solomon, Taye Tadesse, Daniel Nadew, Firezer Girma
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Sorghum is an important crop in semi-arid regions and has shown resilience to drought stress. However, recurrent drought is affecting its productivity. Therefore, it is necessary to explore genes that contribute to drought stress adaptation to increase sorghum productivity. The aim of this study is to evaluate and determine the effect of root system traits, specifically root angle, on drought stress adaptation and grain yield performance in sorghum genotypes. A total of 428 sorghum genotypes from the Ethiopian breeding program were evaluated in three drought-stress environments. Field trials were conducted using a row-column design with three replications. Root system traits were phenotyped using a high-throughput phenotyping platform and analyzed using a row-column design with two replications. Data analysis was performed using R software and regression analysis. The study found significant variations in root system architecture among the sorghum genotypes. Non-stay-green genotypes had a grain yield ranging from 1.63 to 3.1 tons/ha, while stay-green genotypes had a grain yield ranging from 2.4 to 2.9 tons/ha. The analysis of root angle showed that non-stay-green genotypes had an angle ranging from 8.0 to 30.5 degrees, while stay-green genotypes had an angle ranging from 12.0 to 29.0 degrees. Improved varieties exhibited angles between 14.04 and 19.50 degrees. Positive and significant correlations were observed between leaf areas and shoot dry weight, as well as between leaf width and shoot dry weight. Negative correlations were observed between root angle and leaf area, as well as between root angle and root length. This research highlights the importance of root system architecture, particularly root angle traits, in enhancing grain yield production in drought-stressed conditions. It also establishes an association between root angle and grain yield traits for maximizing sorghum productivity.Keywords: roor sysytem architecture, root angle, narrow root angle, wider root angle, drought
Procedia PDF Downloads 7522396 Feasibility of Solar Distillation as Household Water Supply in Saline Zones of Bangladesh
Authors: Md. Rezaul Karim, Md. Ashikur Rahman, Dewan Mahmud Mim
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Scarcity of potable water as the result of rapid climate change and saltwater intrusion in groundwater has been a major problem in the coastal regions over the world. In equinoctial countries like Bangladesh, where sunlight is available for more than 10 hours a day, Solar Distillation provides a promising sustainable way for safe drinking water supply in coastal poor households with negligible major cost and difficulty of construction and maintenance. In this paper, two passive type solar stills- a Conventional Single Slope Solar still (CSS) and a Pyramid Solar Sill (PSS) is used and relationship is established between distill water output corresponding to four different factors- temperature, solar intensity, relative humidity and wind speed for Gazipur, Bangladesh. Comparison is analyzed between the two different still outputs for nine months period (January- September) and efficiency is calculated. Later a thermal mathematical model is developed and the distilled water output for Khulna, Bangladesh is computed. Again, difference between the output of the two cities- Gazipur and Khulna is demonstrated and finally an economic analysis is prepared. The distillation output has a positive correlation with temperature and solar intensity, inverse relation with relative humidity and wind speed has nugatory consequence. The maximum output of Conventional Solar Still is obtained 3.8 L/m2/day and Pyramid still is 4.3 L/m2/day for Gazipur and almost 15% more efficiency is found for Pyramid still. Productivity in Khulna is found almost 20% more than Gazipur. Based on economic analysis, taking 10 BDT, per liter, the net profit, benefit cost ratio, payback period all indicates that both stills are feasible but pyramid still is more feasible than Conventional Still. Finally, for a 3-4 member family, area of 4 m2 is suggested for Conventional Still and 3m2 for Pyramid Solar Still.Keywords: solar distillation, household water supply, saline zones, Bangladesh
Procedia PDF Downloads 27122395 Conjugate Free Convection in a Square Cavity Filled with Nanofluid and Heated from Below by Spatial Wall Temperature
Authors: Ishak Hashim, Ammar Alsabery
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The problem of conjugate free convection in a square cavity filled with nanofluid and heated from below by spatial wall temperature is studied numerically using the finite difference method. Water-based nanofluid with copper nanoparticles are chosen for the investigation. Governing equations are solved over a wide range of nanoparticle volume fraction (0 ≤ φ ≤ 0.2), wave number ((0 ≤ λ ≤ 4) and thermal conductivity ratio (0.44 ≤ Kr ≤ 6). The results presented for values of the governing parameters in terms of streamlines, isotherms and average Nusselt number. It is found that the flow behavior and the heat distribution are clearly enhanced with the increment of the non-uniform heating.Keywords: conjugate free convection, square cavity, nanofluid, spatial temperature
Procedia PDF Downloads 35922394 Influence of Temperature on Properties of MOSFETs
Authors: Azizi Cherifa, O. Benzaoui
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The thermal aspects in the design of power circuits often deserve as much attention as pure electric components aspects as the operating temperature has a direct influence on their static and dynamic characteristics. MOSFET is fundamental in the circuits, it is the most widely used device in the current production of semiconductor components using their honorable performance. The aim of this contribution is devoted to the effect of the temperature on the properties of MOSFETs. The study enables us to calculate the drain current as function of bias in both linear and saturated modes. The effect of temperature is evaluated using a numerical simulation, using the laws of mobility and saturation velocity of carriers as a function of temperature.Keywords: temperature, MOSFET, mobility, transistor
Procedia PDF Downloads 34622393 Implementation of an Image Processing System Using Artificial Intelligence for the Diagnosis of Malaria Disease
Authors: Mohammed Bnebaghdad, Feriel Betouche, Malika Semmani
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Image processing become more sophisticated over time due to technological advances, especially artificial intelligence (AI) technology. Currently, AI image processing is used in many areas, including surveillance, industry, science, and medicine. AI in medical image processing can help doctors diagnose diseases faster, with minimal mistakes, and with less effort. Among these diseases is malaria, which remains a major public health challenge in many parts of the world. It affects millions of people every year, particularly in tropical and subtropical regions. Early detection of malaria is essential to prevent serious complications and reduce the burden of the disease. In this paper, we propose and implement a scheme based on AI image processing to enhance malaria disease diagnosis through automated analysis of blood smear images. The scheme is based on the convolutional neural network (CNN) method. So, we have developed a model that classifies infected and uninfected single red cells using images available on Kaggle, as well as real blood smear images obtained from the Central Laboratory of Medical Biology EHS Laadi Flici (formerly El Kettar) in Algeria. The real images were segmented into individual cells using the watershed algorithm in order to match the images from the Kaagle dataset. The model was trained and tested, achieving an accuracy of 99% and 97% accuracy for new real images. This validates that the model performs well with new real images, although with slightly lower accuracy. Additionally, the model has been embedded in a Raspberry Pi4, and a graphical user interface (GUI) was developed to visualize the malaria diagnostic results and facilitate user interaction.Keywords: medical image processing, malaria parasite, classification, CNN, artificial intelligence
Procedia PDF Downloads 2022392 Aging and Mechanical Behavior of Be-treated 7075 Aluminum Alloys
Authors: Mahmoud M. Tash, S. Alkahtani
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The present study was undertaken to investigate the effect of pre-aging and aging parameters (time and temperature) on the mechanical properties of Al-Mg-Zn (7075) alloys. Ultimate tensile strength, 0.5% offset yield strength and % elongation measurements were carried out on specimens prepared from cast and heat treated 7075 alloys. Aging treatments were carried out for the as solution treated (SHT) specimens (after quenching in warm water). The specimens were aged at different conditions; Natural aging was carried out at room temperature for different periods of time. Double aging was performed for SHT conditions (pre-aged at different time and temperature followed by high temperature aging). Ultimate tensile strength, yield strength and % elongation as a function of different pre-aging and aging parameters are analysed to acquire an understanding of the effects of these variables and their interactions on the mechanical properties of Be-treated 7075 alloys.Keywords: duplex aging treatment, mechanical properties, Al-Mg-Zn (7075) alloys, manufacturing
Procedia PDF Downloads 24022391 A South African Perspective on Artificial Intelligence and Legal Personality
Authors: M. Naidoo
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The concept of moral personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central to the underpinnings of personhood - rather than Western individualism. Personhood in the African context is not an inherent property that a human is born with; rather, it is an ontological journey that one goes on in his or her life with the hopes of attaining personhood. Given the decolonization, projects happening in Africa, and the law-making that is happening in this space within South Africa, it is of paramount importance to consider these views.Keywords: artificial intelligence, bioethics, law, legal personality
Procedia PDF Downloads 8922390 Microstructural Evidences for Exhaustion Theory of Low Temperature Creep in Martensitic Steels
Authors: Nagarjuna Remalli, Robert Brandt
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Down-sizing of combustion engines in automobiles are prevailed owing to required increase in efficiency. This leads to a stress increment on valve springs, which affects their intended function due to an increase in relaxation. High strength martensitic steels are used for valve spring applications. Recent investigations unveiled that low temperature creep (LTC) in martensitic steels obey a logarithmic creep law. The exhaustion theory links the logarithmic creep behavior to an activation energy which is characteristic for any given time during creep. This activation energy increases with creep strain due to barriers of low activation energies exhausted during creep. The assumption of the exhaustion theory is that the material is inhomogeneous in microscopic scale. According to these assumptions it is anticipated that small obstacles (e. g. ε–carbides) having a wide range of size distribution are non-uniformly distributed in the materials. X-ray diffraction studies revealed the presence of ε–carbides in high strength martensitic steels. In this study, high strength martensitic steels that are crept in the temperature range of 75 – 150 °C were investigated with the aid of a transmission electron microscope for the evidence of an inhomogeneous distribution of obstacles having different size to examine the validation of exhaustion theory.Keywords: creep mechanisms, exhaustion theory, low temperature creep, martensitic steels
Procedia PDF Downloads 26322389 Biological Methods to Control Parasitic Weed Phelipanche ramosa L. Pomel in the Field Tomato Crop
Authors: F. Lops, G. Disciglio, A. Carlucci, G. Gatta, L. Frabboni, A. Tarantino, E. Tarantino
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Phelipanche ramosa L. Pomel is a root holoparasitic weed plant of many cultivations, particularly of tomato (Lycopersicum esculentum L.) crop. In Italy, Phelipanche problem is increasing, both in density and in acreage. The biological control of this parasitic weed involves the use of living organisms as numerous fungi and bacteria that can infect the parasitic weed, while it may improve the crop growth. This paper deals with the biocontrol with microorganism, including Arbuscular mycorrhizal (AM) fungi and fungal pathogens as Fusarium oxisporum spp. Colonization of crop roots by AM fungi can provide protection of crops against parasitic weeds because of a reduction in their seed germination and attachment, while F. oxisporum, isolated from diseased broomrape tubercles, proved to be highly virulent on P. ramosa. The experimental trial was carried out in open field at Foggia province (Apulia Region, Southern Italy), during the spring-summer season 2016, in order to evaluate the effect of four biological treatments: AM fungi and Fusarium oxisporum applied in the soil alone or combined together, and Rizosum Max® product, compared with the untreated control, to reduce the P. ramosa infestation in processing tomato crop. The principal results to be drawn from this study under field condition, in contrast of those reported previously under laboratory and greenhouse conditions, show that both AM fungi and F. oxisporum do not provide the reduction of the number of emerged shoots of P. ramosa. This can arise probably from the low efficacy seedling of the agent pathogens for the control of this parasite in the field. On the contrary, the Rizosum Max® product, containing AM fungi and some rizophere bacteria combined with several minerals and organic substances, appears to be most effective for the reduction of P. ramosa infestation.Keywords: Arbuscular mycorrhized fungi, biocontrol methods, Phelipanche ramosa, tomato crop
Procedia PDF Downloads 462