Tantowi Putra Agung Setiawan, Daffa Arrazi, Kenzie Marcell Owen Indrajaya, M. Meiliana, Muhamad Fajar
While flower teas are well-known for their health benefit, little did people know, there are several types of flower tea, and each type has its health benefit. Due to the unavailability of an automated system for classifying Chinese flower tea at the meantime, we then decided to apply the Convolutional Neural Network to help the wider community or flower tea plantation owners to classify flower tea more quickly, accurately, and automated. The purpose of this research is to classify flower tea based on their type by using CNN algorithm. In this research, we used multiple CNN models to find the most suitable architecture. The CNN models compared are ResNet50, SqueezeNet, AlexNet, and ResNet18. The result indicates AlexNet to achieve the highest accuracy of 97.92%
{"title":"A Comparative Study of Convolutional Neural Network Model for Chinese Flower Tea Classification","authors":"Tantowi Putra Agung Setiawan, Daffa Arrazi, Kenzie Marcell Owen Indrajaya, M. Meiliana, Muhamad Fajar","doi":"10.46338/ijetae0123_11","DOIUrl":"https://doi.org/10.46338/ijetae0123_11","url":null,"abstract":"While flower teas are well-known for their health benefit, little did people know, there are several types of flower tea, and each type has its health benefit. Due to the unavailability of an automated system for classifying Chinese flower tea at the meantime, we then decided to apply the Convolutional Neural Network to help the wider community or flower tea plantation owners to classify flower tea more quickly, accurately, and automated. The purpose of this research is to classify flower tea based on their type by using CNN algorithm. In this research, we used multiple CNN models to find the most suitable architecture. The CNN models compared are ResNet50, SqueezeNet, AlexNet, and ResNet18. The result indicates AlexNet to achieve the highest accuracy of 97.92%","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115828736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nor Hidalina Mohd Sabirin, Z. M. Isa, M. Arshad, B. Ismail, Md. Hairul Nizam Talib, E. C. Mid
Harmonics can degrade the power quality of a multilevel inverter by causing the voltage to be distorted and vary from sinusoidal waveforms. Harmonics can be reduced by increasing the number of voltage levels or by employing suitable modulation techniques. In this paper, The Selective Harmonic Elimination Pulse Width Modulation (SHEPWM) modulation method is employed to obtain the optimal switching angles that able to reduce the specific individual harmonic and the Total Harmonic Distortion (THD) in singlephase 7-level Cascaded H-Bridge multilevel inverter. The Animal Migration Optimization (AMO) is proposed to acquire these angles using two difference objective functions. The performance is examined and evaluated. Both objective functions able to determine the optimal switching angles starting from modulation index of 0.34. However, the comparative study demonstratethat objective function number 2 has better performance in term of lowering selective individual harmonics as well as THD.
{"title":"Harmonics Elimination in 7-Level Multilevel Inverter Using Animal Migration Optimization Algorithm with Different Objective Functions","authors":"Nor Hidalina Mohd Sabirin, Z. M. Isa, M. Arshad, B. Ismail, Md. Hairul Nizam Talib, E. C. Mid","doi":"10.46338/ijetae0123_03","DOIUrl":"https://doi.org/10.46338/ijetae0123_03","url":null,"abstract":"Harmonics can degrade the power quality of a multilevel inverter by causing the voltage to be distorted and vary from sinusoidal waveforms. Harmonics can be reduced by increasing the number of voltage levels or by employing suitable modulation techniques. In this paper, The Selective Harmonic Elimination Pulse Width Modulation (SHEPWM) modulation method is employed to obtain the optimal switching angles that able to reduce the specific individual harmonic and the Total Harmonic Distortion (THD) in singlephase 7-level Cascaded H-Bridge multilevel inverter. The Animal Migration Optimization (AMO) is proposed to acquire these angles using two difference objective functions. The performance is examined and evaluated. Both objective functions able to determine the optimal switching angles starting from modulation index of 0.34. However, the comparative study demonstratethat objective function number 2 has better performance in term of lowering selective individual harmonics as well as THD.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117226407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A wireless sensor network (WSN) is an environment monitoring network that collects and transmits data wirelessly to the base station. Due to their inability to be recharged or replaced, sensors face battery constraints. Considering how much energy is wasted by sensors in WSN, this is one of the most popular research topics in WSN. Protocols for improving energy efficiency have been developed to improve the network's energy dissipation and, ultimately, its lifetime. An energy-efficient and throughputenhancing clustering technique is presented in this paper, which is superior to existing protocols based on LEACH. A cluster head in LEACH elected from a cluster that includes nodes with small residual energy will lead to an early death of the network, which will adversely affect its efficiency. The proposed clustering technique, on the other hand, uses the remaining energy of the sensor to make the sensor a cluster head. The base station finds the shortest path between the cluster heads. Through this compound, power dissipation is reduced, which contributes to a longer network lifespan and higher throughput. According to simulations performed with the NS3 simulator, the proposed clustering technique achieves higher network lifetime and throughput compared to some recent clustering protocols, i.e. LEACH, BCE-LEACH, and MO-LEACH.
{"title":"An Intelligent Energy-Efficient Clustering Technique to Maximize Wireless Sensor Network Lifetime","authors":"Almamoon Alauthman, W. Nik, N. Mahiddin","doi":"10.46338/ijetae0123_01","DOIUrl":"https://doi.org/10.46338/ijetae0123_01","url":null,"abstract":"A wireless sensor network (WSN) is an environment monitoring network that collects and transmits data wirelessly to the base station. Due to their inability to be recharged or replaced, sensors face battery constraints. Considering how much energy is wasted by sensors in WSN, this is one of the most popular research topics in WSN. Protocols for improving energy efficiency have been developed to improve the network's energy dissipation and, ultimately, its lifetime. An energy-efficient and throughputenhancing clustering technique is presented in this paper, which is superior to existing protocols based on LEACH. A cluster head in LEACH elected from a cluster that includes nodes with small residual energy will lead to an early death of the network, which will adversely affect its efficiency. The proposed clustering technique, on the other hand, uses the remaining energy of the sensor to make the sensor a cluster head. The base station finds the shortest path between the cluster heads. Through this compound, power dissipation is reduced, which contributes to a longer network lifespan and higher throughput. According to simulations performed with the NS3 simulator, the proposed clustering technique achieves higher network lifetime and throughput compared to some recent clustering protocols, i.e. LEACH, BCE-LEACH, and MO-LEACH.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126670543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joseph Sekyi – Ansah, S. Eduku, Daniel Minnow Maclar
Research depicts that vehicular accident is inevitable, especially during long-distance driving journeys due to occurrence such as dehydration and discomfort owing to the inadequate or poor operating performance of car airconditioning systems which can result in loss of the driver’s attention on the road. However, the aforementioned research gap or problem needs to be addressed to ensure the efficient operation of the car air-conditioning system to avert vehicular accidents. Hence, the goal of this research is to utilize a microcontroller to automatically control the car airconditioning system to ensure enhanced operating performance. Moreover, the key merit of this research is to assist drivers by preventing them from losing attention on the road due to a phenomenon such as dehydration and discomfort, especially, during long-distance driving journeys, which can cause vehicular accidents. Besides, another imperative component of this research is to automatically control, thus closing the vehicle’s window louvre once the air conditioner is in operation or turned on to ensure efficient utilization of energy (fuel) of the vehicle and ensure that the ambience in the vehicle is pretty comfortable for the passengers on board. The automated power window system is comprehensively verified by the proteus software. Nonetheless, the results via the simulation depict that the automated power window circuit considered in this paper can effectively and automatically close the vehicle’s window louvre once the air conditioner is turned on.
{"title":"Microcontroller Integration in an Automated Power Window Circuit System for Automobile Air Conditioning","authors":"Joseph Sekyi – Ansah, S. Eduku, Daniel Minnow Maclar","doi":"10.46338/ijetae0123_06","DOIUrl":"https://doi.org/10.46338/ijetae0123_06","url":null,"abstract":"Research depicts that vehicular accident is inevitable, especially during long-distance driving journeys due to occurrence such as dehydration and discomfort owing to the inadequate or poor operating performance of car airconditioning systems which can result in loss of the driver’s attention on the road. However, the aforementioned research gap or problem needs to be addressed to ensure the efficient operation of the car air-conditioning system to avert vehicular accidents. Hence, the goal of this research is to utilize a microcontroller to automatically control the car airconditioning system to ensure enhanced operating performance. Moreover, the key merit of this research is to assist drivers by preventing them from losing attention on the road due to a phenomenon such as dehydration and discomfort, especially, during long-distance driving journeys, which can cause vehicular accidents. Besides, another imperative component of this research is to automatically control, thus closing the vehicle’s window louvre once the air conditioner is in operation or turned on to ensure efficient utilization of energy (fuel) of the vehicle and ensure that the ambience in the vehicle is pretty comfortable for the passengers on board. The automated power window system is comprehensively verified by the proteus software. Nonetheless, the results via the simulation depict that the automated power window circuit considered in this paper can effectively and automatically close the vehicle’s window louvre once the air conditioner is turned on.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130259514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Anam, Indah Yanti, Z. Fitriah, M. H. A. M. Assidiq
Early blight is one of diseases that infects tomato leaves. This disease causes a decrease in the production of tomato plants. The early detection of this diseases is very important to maintain the tomato production. Monitoring tomato leaves health manually in large area is very time-consuming and inefficient. The drones and computer vision technology give an alternative in solving this problem. One of the important steps in detecting the tomato leaf disease based on computer vision is the segmentation area of the tomato leaf into the healthy and diseased tomato leaf. The K-means clustering offers an image segmentation method that is simple, fast and works unsupervised. However, the solutions of the K-means clustering often be trapped into the local optimum. The Particle Swarm Optimization (PSO) offers a solution of this problem. However, the performance of PSO depends on the particle velocity of the PSO, if the particle velocity is not determined precisely then the PSO will converge prematurely. Fuzzy Adaptive Turbulence Particle Swarm Optimization (FATPSO) is able to control minimum velocity the PSO particles adaptively for overcoming the premature convergence problem in PSO. The good features from image will increase the accuracy of machine learning algorithm. For this reason, these papers the tomato leaf segmentation based on the FATPSO clustering algorithm with multi features. The fitness function of FATPSO uses an objective function of K-means. The experiments use the image taken manually from garden tomatoes. The images have good quality but they have many varieties in size and color. The next research should be considered to use the image taken by drone to guarantee a robust method of image quality produced by drones. The experimental results show that the FATPSO clustering algorithm with multi features has a better performance than the PSO algorithm with multi feature in the tomato leaf disease segmentation
{"title":"Tomato Leaf Disease Segmentation Using Clustering Method Based on FATPSO with Multi Features","authors":"S. Anam, Indah Yanti, Z. Fitriah, M. H. A. M. Assidiq","doi":"10.46338/ijetae0123_04","DOIUrl":"https://doi.org/10.46338/ijetae0123_04","url":null,"abstract":"Early blight is one of diseases that infects tomato leaves. This disease causes a decrease in the production of tomato plants. The early detection of this diseases is very important to maintain the tomato production. Monitoring tomato leaves health manually in large area is very time-consuming and inefficient. The drones and computer vision technology give an alternative in solving this problem. One of the important steps in detecting the tomato leaf disease based on computer vision is the segmentation area of the tomato leaf into the healthy and diseased tomato leaf. The K-means clustering offers an image segmentation method that is simple, fast and works unsupervised. However, the solutions of the K-means clustering often be trapped into the local optimum. The Particle Swarm Optimization (PSO) offers a solution of this problem. However, the performance of PSO depends on the particle velocity of the PSO, if the particle velocity is not determined precisely then the PSO will converge prematurely. Fuzzy Adaptive Turbulence Particle Swarm Optimization (FATPSO) is able to control minimum velocity the PSO particles adaptively for overcoming the premature convergence problem in PSO. The good features from image will increase the accuracy of machine learning algorithm. For this reason, these papers the tomato leaf segmentation based on the FATPSO clustering algorithm with multi features. The fitness function of FATPSO uses an objective function of K-means. The experiments use the image taken manually from garden tomatoes. The images have good quality but they have many varieties in size and color. The next research should be considered to use the image taken by drone to guarantee a robust method of image quality produced by drones. The experimental results show that the FATPSO clustering algorithm with multi features has a better performance than the PSO algorithm with multi feature in the tomato leaf disease segmentation","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124439124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
—Recently, many technological improvement apply in the discovery of various designs of haptic devices. Several mechanism structures including serial, parallel, and hybrid-kinematic manipulators can be considered for making a haptics device. The most successful haptic mechanisms are parallel-type, because of low moving inertia, large force reflection, and high stiffness. This research shows the 6-DOF parallel haptics device based on the parallel mechanism using a translation driver motor mounted on each leg. Firstly, we introduce a 6-DOF parallel mechanism using a translation driver motor haptics device model. Due to the unsure parameters, we focus on solving the mathematics model with the nonlinear parameters of the 6-DOF parallel mechanism. Secondly, to fix the kinematics and dynamics nonlinear uncertainties parameters, the SMCNN controller for 6-DOF parallel mechanism application using a translation driver motor is designed. The Sliding model control base on artificial intelligence neural network is used to calculate the unsure factors. In this technique, to prove the stability of the system the Lyapunop theory is used. Finally, the authors the simulation results of two control algorithms with different uncertain components are presented and comparing them to demonstrate the effectiveness of the new control method. The control method is demonstrated by way of implementing the set of rules in artificial surroundings with realistic parameters, in which the received consequences are fairly promising. The obtained from SMCNN algorithm results are highly promising and accurate.
{"title":"Dynamic Analysis and Design of an SMCNN of a 6-DOF Parallel Mechanisms using Translation Driver Motor","authors":"Doan Van Tuan, Nguyen Luong Thien, P. Ngoc","doi":"10.46338/ijetae0123_09","DOIUrl":"https://doi.org/10.46338/ijetae0123_09","url":null,"abstract":"—Recently, many technological improvement apply in the discovery of various designs of haptic devices. Several mechanism structures including serial, parallel, and hybrid-kinematic manipulators can be considered for making a haptics device. The most successful haptic mechanisms are parallel-type, because of low moving inertia, large force reflection, and high stiffness. This research shows the 6-DOF parallel haptics device based on the parallel mechanism using a translation driver motor mounted on each leg. Firstly, we introduce a 6-DOF parallel mechanism using a translation driver motor haptics device model. Due to the unsure parameters, we focus on solving the mathematics model with the nonlinear parameters of the 6-DOF parallel mechanism. Secondly, to fix the kinematics and dynamics nonlinear uncertainties parameters, the SMCNN controller for 6-DOF parallel mechanism application using a translation driver motor is designed. The Sliding model control base on artificial intelligence neural network is used to calculate the unsure factors. In this technique, to prove the stability of the system the Lyapunop theory is used. Finally, the authors the simulation results of two control algorithms with different uncertain components are presented and comparing them to demonstrate the effectiveness of the new control method. The control method is demonstrated by way of implementing the set of rules in artificial surroundings with realistic parameters, in which the received consequences are fairly promising. The obtained from SMCNN algorithm results are highly promising and accurate.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114554091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wan Azman Bin Wan Ahmad, Mohd Azrul Hisham Mohd Adib, Mohd Husaini bin Mohd Jaafar, Mon Redee Sut Txi
Competitive anxiety is the greatest challenge for athletes, especially in games involving big competitions. This study aims to formulate athletes' anxiety based on their sports performance. Therefore, this study found three parameters influencing athletes' anxiety: heart rate, blood pressure and muscle tension. Hence, the data collection from three phases, namely before, during and after the competition, was recorded. The data were analyzed based on the anxiety index formulation to obtain the athletes' anxiety index rate. By comparing the reading pace of normal persons to the results of this data analysis, the researcher created a set of athlete anxiety indexes. For future research, an anxiety monitoring system prototype based on IoT technology will be created using coding from the athlete's anxiety index to ensure that the coach can notice the athlete's anxiety rate early. With this study, it is believed that future sports athlete performance in the country will be more consistent.
{"title":"Formulation of Anxiety Concentration Index on Athletes Performances using Application of IoT Device","authors":"Wan Azman Bin Wan Ahmad, Mohd Azrul Hisham Mohd Adib, Mohd Husaini bin Mohd Jaafar, Mon Redee Sut Txi","doi":"10.46338/ijetae0123_05","DOIUrl":"https://doi.org/10.46338/ijetae0123_05","url":null,"abstract":"Competitive anxiety is the greatest challenge for athletes, especially in games involving big competitions. This study aims to formulate athletes' anxiety based on their sports performance. Therefore, this study found three parameters influencing athletes' anxiety: heart rate, blood pressure and muscle tension. Hence, the data collection from three phases, namely before, during and after the competition, was recorded. The data were analyzed based on the anxiety index formulation to obtain the athletes' anxiety index rate. By comparing the reading pace of normal persons to the results of this data analysis, the researcher created a set of athlete anxiety indexes. For future research, an anxiety monitoring system prototype based on IoT technology will be created using coding from the athlete's anxiety index to ensure that the coach can notice the athlete's anxiety rate early. With this study, it is believed that future sports athlete performance in the country will be more consistent.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115181000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aims to develop an eddy current testing (ECT) probe that generates eddy current signals when a coil is placed above copper101 metal testing with and without nonconductive coating and the presence of lift-off height, i.e., 0, 2.5, 5.0, 7.5, and 10.0 0.5 mm. Then, the metal test with a variety of thicknesses, i.e., 1.5, 3.0, and 5.0 0.5 mm, and with varies of surface defects, i.e., 10, 20, and 30 0.5 mm, engraved on the metal testing. The coil probe is a rodshaped solenoid coil designed with an iron core with 65 mm length, 5 mm area, and 200 N turns. It demonstrates how the rod-shaped solenoid coil may be used to detect various surface defects on copper101 (C101). The optimal frequencies for C101 are 7.850 MHz. In conclusion, the output voltage signals for larger surface defect sizes increase but decrease as the thickness becomes thicker. Furthermore, as the lift-off height increases, the output voltage for both coated and non-coated metal decreases accordingly. Therefore, besides comparing the output voltage for coated and non-coated metals, there are minor differences which shows that the ECT technique in this studyis capableto detect surface defects appropriately.
{"title":"Lift-Off Effect Evaluation by Using Eddy Current Testing Technique on Copper (C101)","authors":"F. Sulaiman, Syafiqa Putri Adlina Harun, E. Eldy","doi":"10.46338/ijetae0123_07","DOIUrl":"https://doi.org/10.46338/ijetae0123_07","url":null,"abstract":"This study aims to develop an eddy current testing (ECT) probe that generates eddy current signals when a coil is placed above copper101 metal testing with and without nonconductive coating and the presence of lift-off height, i.e., 0, 2.5, 5.0, 7.5, and 10.0 0.5 mm. Then, the metal test with a variety of thicknesses, i.e., 1.5, 3.0, and 5.0 0.5 mm, and with varies of surface defects, i.e., 10, 20, and 30 0.5 mm, engraved on the metal testing. The coil probe is a rodshaped solenoid coil designed with an iron core with 65 mm length, 5 mm area, and 200 N turns. It demonstrates how the rod-shaped solenoid coil may be used to detect various surface defects on copper101 (C101). The optimal frequencies for C101 are 7.850 MHz. In conclusion, the output voltage signals for larger surface defect sizes increase but decrease as the thickness becomes thicker. Furthermore, as the lift-off height increases, the output voltage for both coated and non-coated metal decreases accordingly. Therefore, besides comparing the output voltage for coated and non-coated metals, there are minor differences which shows that the ECT technique in this studyis capableto detect surface defects appropriately.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130709642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Elhussieny, S. O. Elshabrawy, Noralizawati Mohamed, I. Fahim, L. Said, A. Radwan
- Dye is considered a carcinogenic matter. So, it is extremely important to treat the wastewater which contains the dye by detecting eco-friendly technologies to protect the environment from any negative impacts, the resources of natural water, and facing water shortage. The treatment of wastewater can be applied by using low-cost by-products from various sources such as domestic, industrial, and agricultural sectors. They enable the elimination of pollutants from wastewater and support the reduction, recovery, and reuse of waste. This study represents current membrane technologies for dye removal using the WAVE simulation software, provided by Dupont to study the performance, process parameters, and operating conditions. The WAVE simulation software explained also the benefits and drawbacks of various treatment methods. This research aims to investigate the physical properties and efficiency of the synthesized composite membranes and determine their feasibility for use in membrane filtration.
{"title":"Evaluation of Membranes’ Performance in Wastewater Treatment by WAVE Simulation","authors":"A. Elhussieny, S. O. Elshabrawy, Noralizawati Mohamed, I. Fahim, L. Said, A. Radwan","doi":"10.46338/ijetae0123_08","DOIUrl":"https://doi.org/10.46338/ijetae0123_08","url":null,"abstract":"- Dye is considered a carcinogenic matter. So, it is extremely important to treat the wastewater which contains the dye by detecting eco-friendly technologies to protect the environment from any negative impacts, the resources of natural water, and facing water shortage. The treatment of wastewater can be applied by using low-cost by-products from various sources such as domestic, industrial, and agricultural sectors. They enable the elimination of pollutants from wastewater and support the reduction, recovery, and reuse of waste. This study represents current membrane technologies for dye removal using the WAVE simulation software, provided by Dupont to study the performance, process parameters, and operating conditions. The WAVE simulation software explained also the benefits and drawbacks of various treatment methods. This research aims to investigate the physical properties and efficiency of the synthesized composite membranes and determine their feasibility for use in membrane filtration.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133454945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
—Standard datasets in deep learning-basedimage classification usually provide two favorable conditions for design: preservation of visual homogeneity of each category and uniform distribution of sample images. These conditions are not assured in a dataset of plant images. Two different species of plants under the same genus look very similar and the number of collectible images has a large variation over species.Visual similarity, however, can be turned into advantage in hierarchical approach, by assigning two-fold labels of species and genus, in two phases ofrough classification of genera and fine classification of species. We propose a hierarchical classification in which the concatenation scheme is augmented with a channel attention which focuses on the sibling relation of species. We compared our method with flat classification and conventional hierarchical classification. The test was on a PlantNet-300K dataset 300k images, composed of 303 genera and 1081 species. In experimental results, the channel attention layers lead to stable discerningof the minute difference among visually similar species. The proposed hierarchical classification method outperforms both the flat classification and the conventional hierarchical classification.
{"title":"Deep Attention-based Classification of Plant Images with Hierarchical Similarity and Imbalanced Distribution","authors":"Hyounguk Kim, Yong Cheol Kim","doi":"10.46338/ijetae0123_02","DOIUrl":"https://doi.org/10.46338/ijetae0123_02","url":null,"abstract":"—Standard datasets in deep learning-basedimage classification usually provide two favorable conditions for design: preservation of visual homogeneity of each category and uniform distribution of sample images. These conditions are not assured in a dataset of plant images. Two different species of plants under the same genus look very similar and the number of collectible images has a large variation over species.Visual similarity, however, can be turned into advantage in hierarchical approach, by assigning two-fold labels of species and genus, in two phases ofrough classification of genera and fine classification of species. We propose a hierarchical classification in which the concatenation scheme is augmented with a channel attention which focuses on the sibling relation of species. We compared our method with flat classification and conventional hierarchical classification. The test was on a PlantNet-300K dataset 300k images, composed of 303 genera and 1081 species. In experimental results, the channel attention layers lead to stable discerningof the minute difference among visually similar species. The proposed hierarchical classification method outperforms both the flat classification and the conventional hierarchical classification.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115197659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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