Pub Date : 2024-04-03DOI: 10.17485/ijst/v17i14.2651
Pushparani S Janes, P. L. Chithra
Background/Objectives: Enhancing agricultural productivity is crucial for fostering economic growth. Plant diseases significantly threaten crops, necessitating timely detection to mitigate adverse impacts on quality, quantity, and overall productivity. This research addresses the importance of early disease detection in agriculture and proposes an innovative method utilizing Jacobian Polynomial and Laplacian Function for precise identification. Methods: Efficient monitoring of large-scale crop farms with minimal workforce is essential. To achieve this, an automatic method for plant disease detection is proposed. The method leverages Jacobian polynomials to expand input features, mitigating correlation issues among input vectors. The expanded Jacobi polynomial is the input vector for a backpropagation algorithm with a novel activation function based on the Laplacian function. Findings: The efficacy of the proposed JPLF model is demonstrated through the accurate identification of leaf diseases, achieving a high testing accuracy of 92.07%. Comparative analysis with existing models, such as CNN with MobileNet V2 (85.38%) and the IoU model (83.75%), highlights the superiority of the JPLF model in plant disease detection. Novelty: To overcome the limitations of existing approaches, the incorporation of Jacobian polynomials plays a pivotal role in expanding input features. This expansion aids in eliminating correlations among input vectors, enhancing the efficacy of disease detection. The proposed model, Jacobi Polynomial and Laplacian Function (JPLF) introduces a unique activation function based on the Laplacian function, improving accuracy. Keywords: Plant Disease Detection, Jacobi Polynomial, Laplacian Transform, Deep Learning Model, Feature Expansion
{"title":"A Novel Deep Convolutional Neural Network Approach using Jacobi Polynomial and Laplacian Function (JPLF) in Recognition of Plant Leaf Disease","authors":"Pushparani S Janes, P. L. Chithra","doi":"10.17485/ijst/v17i14.2651","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.2651","url":null,"abstract":"Background/Objectives: Enhancing agricultural productivity is crucial for fostering economic growth. Plant diseases significantly threaten crops, necessitating timely detection to mitigate adverse impacts on quality, quantity, and overall productivity. This research addresses the importance of early disease detection in agriculture and proposes an innovative method utilizing Jacobian Polynomial and Laplacian Function for precise identification. Methods: Efficient monitoring of large-scale crop farms with minimal workforce is essential. To achieve this, an automatic method for plant disease detection is proposed. The method leverages Jacobian polynomials to expand input features, mitigating correlation issues among input vectors. The expanded Jacobi polynomial is the input vector for a backpropagation algorithm with a novel activation function based on the Laplacian function. Findings: The efficacy of the proposed JPLF model is demonstrated through the accurate identification of leaf diseases, achieving a high testing accuracy of 92.07%. Comparative analysis with existing models, such as CNN with MobileNet V2 (85.38%) and the IoU model (83.75%), highlights the superiority of the JPLF model in plant disease detection. Novelty: To overcome the limitations of existing approaches, the incorporation of Jacobian polynomials plays a pivotal role in expanding input features. This expansion aids in eliminating correlations among input vectors, enhancing the efficacy of disease detection. The proposed model, Jacobi Polynomial and Laplacian Function (JPLF) introduces a unique activation function based on the Laplacian function, improving accuracy. Keywords: Plant Disease Detection, Jacobi Polynomial, Laplacian Transform, Deep Learning Model, Feature Expansion","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"26 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140747947","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}
Pub Date : 2024-04-03DOI: 10.17485/ijst/v17i14.118
Shailesh Sangle, R. Sedamkar
Objectives: The primary objectives of this study encompass the enhancement of election campaign strategies through the synthesis of sentiment-laden slogans derived from Twitter data. This is achieved by employing a novel Hybrid SDG-LSTM model, aiming to improve sentiment prediction accuracy and communication efficacy in the context of political campaigns. Methods: The process of slogan generation relies on sentiment prediction derived from sentiment-laden tweets. The proposed sentiment analysis methods for election campaign slogans encompass Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). A novel approach is introduced through the Hybrid SDG-LSTM model, leveraging the combination of Self-Distillation Guidance (SDG) with LSTM to enhance sentiment prediction accuracy and efficiency. This innovative method aims to provide a more robust and effective means of analyzing and generating slogans for election campaigns. Findings: The performance assessment of Deep Learning models, GRU, LSTM, and the Hybrid architecture, unveiled compelling outcomes. GRU showcased a commendable accuracy of 92.98%, while LSTM impressed with 95.91%. Remarkably, the Hybrid Spatial LSTM with GRU surpassed both, achieving perfection with 100% accuracy, precision, recall, and an exceptionally low loss of 0.0. These results underscore the superior performance and efficacy of the Hybrid model in sentiment analysis tasks. Novelty: The novelty of this research is encapsulated in the introduction of the Hybrid Spatial LSTM with GRU model, which demonstrates groundbreaking 100% accuracy, surpassing current models. This innovation capitalizes on the synergistic fusion of spatial attention mechanisms and the dynamic nature of GRU, marking a substantial advancement and establishing a new benchmark for highly accurate predictions in the domain of sentiment analysis. Keywords: Slogan Generation, Sentiment Analysis, Election Campaign, Deep Learning, LSTM, GRU
{"title":"Synthesis of Slogans with Predicted Sentiment from Twitter using a Novel Hybrid SDG-LSTM Model for Election Campaigns","authors":"Shailesh Sangle, R. Sedamkar","doi":"10.17485/ijst/v17i14.118","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.118","url":null,"abstract":"Objectives: The primary objectives of this study encompass the enhancement of election campaign strategies through the synthesis of sentiment-laden slogans derived from Twitter data. This is achieved by employing a novel Hybrid SDG-LSTM model, aiming to improve sentiment prediction accuracy and communication efficacy in the context of political campaigns. Methods: The process of slogan generation relies on sentiment prediction derived from sentiment-laden tweets. The proposed sentiment analysis methods for election campaign slogans encompass Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). A novel approach is introduced through the Hybrid SDG-LSTM model, leveraging the combination of Self-Distillation Guidance (SDG) with LSTM to enhance sentiment prediction accuracy and efficiency. This innovative method aims to provide a more robust and effective means of analyzing and generating slogans for election campaigns. Findings: The performance assessment of Deep Learning models, GRU, LSTM, and the Hybrid architecture, unveiled compelling outcomes. GRU showcased a commendable accuracy of 92.98%, while LSTM impressed with 95.91%. Remarkably, the Hybrid Spatial LSTM with GRU surpassed both, achieving perfection with 100% accuracy, precision, recall, and an exceptionally low loss of 0.0. These results underscore the superior performance and efficacy of the Hybrid model in sentiment analysis tasks. Novelty: The novelty of this research is encapsulated in the introduction of the Hybrid Spatial LSTM with GRU model, which demonstrates groundbreaking 100% accuracy, surpassing current models. This innovation capitalizes on the synergistic fusion of spatial attention mechanisms and the dynamic nature of GRU, marking a substantial advancement and establishing a new benchmark for highly accurate predictions in the domain of sentiment analysis. Keywords: Slogan Generation, Sentiment Analysis, Election Campaign, Deep Learning, LSTM, GRU","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"397 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140749859","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}
Pub Date : 2024-04-03DOI: 10.17485/ijst/v17i14.3148
Mohammed Naser Farooqui, Nilesh G Patil, A. S. Gore
Objective: To maximize the cutting rates and to minimize and width of cut (Kerf) by optimizing the process parameters for wire EDM machining of Si3N4-TiN ceramic composite utilizing zinc coated brass wire optimizing the process parameters by applying Response Surface Methodology using Central Composite Design Technique. Methods: The input parameters, namely, peak current, short pulse duration, and pulse on time duration were varied over five different levels, in order to conduct the studies. The distinctive response characteristics, such as cutting rates and width of cut, are investigated, and optimized using Response Surface Methodology (RSM), which is based on Design of Experiments (DOE). ANOVA was applied to both predictive modeling and the identification of significant variables in order to assess the effectiveness of the model. In the experiments, a coated brass wire electrode was employed in the center composite design. Findings: Comparing the cutting rates with a plain brass electrode, the increases are 4.39% and 16.67%, respectively. The pulse-on time and pulse current are recognized as the two most crucial input parameters; cutting rate rises with increasing current. A coated brass wire with negative tool polarity achieved a maximum cutting rate of 69.72 mm2/min at a peak current of 320A, 1.2 μs of on time pulse duration, the ideal Kerf of 0.35mm was obtained. The % error of RSM predicted and actual is 5.36% for cutting rate and 1.05% for Kerf. Novelty: There is no literature available on the machining of Si3N4-TiN using coated brass wire, for Kerf width and cutting speeds. The zinc-coated brass wire electrode improves the cutting rates and reduces the Kerf significantly for Si3N4-TiN ceramic composite. Keywords: Si3N4-TiN, CR, Kerf, RSM, ANOVA
{"title":"Investigation into Optimizing of Machining Parameters using RSM for Si3N4 -TiN Ceramic C omposites by WEDM","authors":"Mohammed Naser Farooqui, Nilesh G Patil, A. S. Gore","doi":"10.17485/ijst/v17i14.3148","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.3148","url":null,"abstract":"Objective: To maximize the cutting rates and to minimize and width of cut (Kerf) by optimizing the process parameters for wire EDM machining of Si3N4-TiN ceramic composite utilizing zinc coated brass wire optimizing the process parameters by applying Response Surface Methodology using Central Composite Design Technique. Methods: The input parameters, namely, peak current, short pulse duration, and pulse on time duration were varied over five different levels, in order to conduct the studies. The distinctive response characteristics, such as cutting rates and width of cut, are investigated, and optimized using Response Surface Methodology (RSM), which is based on Design of Experiments (DOE). ANOVA was applied to both predictive modeling and the identification of significant variables in order to assess the effectiveness of the model. In the experiments, a coated brass wire electrode was employed in the center composite design. Findings: Comparing the cutting rates with a plain brass electrode, the increases are 4.39% and 16.67%, respectively. The pulse-on time and pulse current are recognized as the two most crucial input parameters; cutting rate rises with increasing current. A coated brass wire with negative tool polarity achieved a maximum cutting rate of 69.72 mm2/min at a peak current of 320A, 1.2 μs of on time pulse duration, the ideal Kerf of 0.35mm was obtained. The % error of RSM predicted and actual is 5.36% for cutting rate and 1.05% for Kerf. Novelty: There is no literature available on the machining of Si3N4-TiN using coated brass wire, for Kerf width and cutting speeds. The zinc-coated brass wire electrode improves the cutting rates and reduces the Kerf significantly for Si3N4-TiN ceramic composite. Keywords: Si3N4-TiN, CR, Kerf, RSM, ANOVA","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"56 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140748680","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}
Pub Date : 2024-04-03DOI: 10.17485/ijst/v17i14.168
Sushila Sushila, Parveen Kumar
Objectives: The present study is aimed to investigate electrocoagulation of domestic wastewater and assessment of pollutants removal efficiency for potential reuse in agriculture. Methods: The electrocoagulation treatment of domestic wastewater with Fe – Fe electrodes was performed under optimal conditions of pH (8.0), current density (0.6 mA/cm2), treatment time (45 minutes), and NaCl dose (2.8 g/L) in a slurry type of reactor. The primary clarified and biotreated domestic wastewaters were subjected to electrocoagulation with Direct Current (DC) as power source. Findings: There was observed higher pollutants removal efficiency from the biotreated wastewater as compared with the primary clarified wastewater after electrocoagulation. The treated wastewaters showed significant removal of pollutants in terms of BOD (79.5% – 87.9%), COD (86.8% – 89.5%), TDS (87.4% – 89.9%), TSS (66.7% – 75.3%), conductivity (77.8% – 78.4%), turbidity (74% – 81.2%), colour (77.7% – 86.2%), nitrates (44.1% – 51.7%), and phosphates (48.7% – 55.9%) after electrocoagulation treatment. Electrocoagulation considerably improved the biodegradability index of the primary clarified (0.59 to 0.92) and biotreated (0.69 to 0.8) wastewaters. This indicates easy removal of the pollutants further by biological processes in the aquatic ecosystems. Electrocoagulation demonstrated potential for removal of pollution from the domestic wastewater for productive reuse in agriculture and urban areas. Novelty: There exist few studies of use of electrochemical process for treatment and reuse of domestic wastewater. The treated waters complied with the regulatory standards and had satisfactory quality for reuse in agriculture and urban activities. Keywords: Electrocoagulation, Domestic wastewater, Biodegradability index, Agricultural reuse, National Green Tribunal
{"title":"Pollution Load Reduction from Domestic Wastewater with Electrocoagulation Process for Agricultural Reuse","authors":"Sushila Sushila, Parveen Kumar","doi":"10.17485/ijst/v17i14.168","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.168","url":null,"abstract":"Objectives: The present study is aimed to investigate electrocoagulation of domestic wastewater and assessment of pollutants removal efficiency for potential reuse in agriculture. Methods: The electrocoagulation treatment of domestic wastewater with Fe – Fe electrodes was performed under optimal conditions of pH (8.0), current density (0.6 mA/cm2), treatment time (45 minutes), and NaCl dose (2.8 g/L) in a slurry type of reactor. The primary clarified and biotreated domestic wastewaters were subjected to electrocoagulation with Direct Current (DC) as power source. Findings: There was observed higher pollutants removal efficiency from the biotreated wastewater as compared with the primary clarified wastewater after electrocoagulation. The treated wastewaters showed significant removal of pollutants in terms of BOD (79.5% – 87.9%), COD (86.8% – 89.5%), TDS (87.4% – 89.9%), TSS (66.7% – 75.3%), conductivity (77.8% – 78.4%), turbidity (74% – 81.2%), colour (77.7% – 86.2%), nitrates (44.1% – 51.7%), and phosphates (48.7% – 55.9%) after electrocoagulation treatment. Electrocoagulation considerably improved the biodegradability index of the primary clarified (0.59 to 0.92) and biotreated (0.69 to 0.8) wastewaters. This indicates easy removal of the pollutants further by biological processes in the aquatic ecosystems. Electrocoagulation demonstrated potential for removal of pollution from the domestic wastewater for productive reuse in agriculture and urban areas. Novelty: There exist few studies of use of electrochemical process for treatment and reuse of domestic wastewater. The treated waters complied with the regulatory standards and had satisfactory quality for reuse in agriculture and urban activities. Keywords: Electrocoagulation, Domestic wastewater, Biodegradability index, Agricultural reuse, National Green Tribunal","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"567 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140749712","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}
Pub Date : 2024-04-03DOI: 10.17485/ijst/v17i14.3033
J. Prasad, Vasim Babu, M. Kasiselvanathan, K. Gurumoorthy
Objectives: This work objective is to construct an FPGA-based 16x16 Vedic multiplier and assess the performance of the multiplier using three distinct architectures: pipeline, wave pipeline, and modified wave pipeline in terms of delay and clock skew. Methods: The 16 × 16 Vedic multiplier was constructed and designed through four numbers of an 8x8 Vedic multiplier. For the 16x16 Vedic multiplier, the 3-stage pipeline and wave pipeline techniques are applied, and the delay performances of the Vedic multiplier are compared. Delay optimization: In the wave pipeline Vedic multiplier architecture, the delay is decreased by inserting the known delay on the longest path delay between the multiplier and adder. Clock skew optimization: The clock skew issue of the wave pipeline Vedic multiplier architecture is minimized by adjusting the setup time violation of the clock signal that is connected to the input and output registers. Findings: The delay performance of the Vedic multiplier was evaluated by the synthesis tools Xilinx 12.1, Xilinx ISE 14.2, and Altera, and based on the synthesis report, the Xilinx synthesis tool offers 73.71% delay performance for the pipeline approach and 53.39% for the wave pipeline approach compared to the Altera tool. Further delay is reduced by the proposed modified wave pipeline approach, which saves 2.122 ns of delay compared to the wave pipeline architecture. The clock skew performance was analyzed using the Time Quest timing analyzer tool, and it was minimized to 0.035 from 0.048 compared to the wave pipeline approach. Novelty: In this work, the modified wave pipeline approach has been applied to the existing Vedic multiplier architecture, and it offers less delay as well as less clock skew compared to the existing method. Hence, the performance of the Vedic multiplier with a modified wave pipelined approach was evaluated through a 3-tap FIR filter by applying a vibroarthrography signal. Keywords: Pipeline, Wave Pipeline, Vedic Multiplier, Clock skew, Set up violation, Altera quartex- II Time quest timing analyzer tool
目标：这项工作的目标是构建一个基于 FPGA 的 16x16 Vedic 乘法器，并评估使用三种不同架构（流水线、波流水线和改进的波流水线）的乘法器在延迟和时钟偏移方面的性能。方法通过对 8x8 Vedic 乘法器的四个编号构建和设计了 16×16 Vedic 乘法器。对于 16x16 Vedic 乘法器，应用了 3 级流水线和波形流水线技术，并比较了 Vedic 乘法器的延迟性能。延迟优化：在波形流水线吠陀乘法器架构中，通过在乘法器和加法器之间的最长路径延迟上插入已知延迟来减少延迟。时钟偏移优化：通过调整连接到输入和输出寄存器的时钟信号的设置时间误差，将波形流水线吠陀乘法器架构的时钟偏移问题降至最低。研究结果综合工具 Xilinx 12.1、Xilinx ISE 14.2 和 Altera 对 Vedic 乘法器的延迟性能进行了评估，根据综合报告，与 Altera 工具相比，Xilinx 综合工具的流水线方法延迟性能为 73.71%，波形流水线方法为 53.39%。改进的波形流水线方法进一步减少了延迟，与波形流水线架构相比，可节省 2.122 ns 的延迟。使用 Time Quest 时序分析工具分析了时钟偏移性能，与波形流水线方法相比，时钟偏移从 0.048 降至 0.035。新颖性：在这项工作中，修改后的波形流水线方法被应用于现有的吠陀乘法器架构，与现有方法相比，它提供了更少的延迟和更少的时钟偏移。因此，通过一个 3 抽头 FIR 滤波器，应用振动造影信号评估了采用改进波形流水线方法的吠陀乘法器的性能。关键词流水线、波形流水线、吠陀乘法器、时钟偏移、设置违规、Altera quartex- II 时序分析工具
{"title":"Pipelined and Wave Pipelined Approach Based Comparative Analysis for 16x16 Vedic Multiplier","authors":"J. Prasad, Vasim Babu, M. Kasiselvanathan, K. Gurumoorthy","doi":"10.17485/ijst/v17i14.3033","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.3033","url":null,"abstract":"Objectives: This work objective is to construct an FPGA-based 16x16 Vedic multiplier and assess the performance of the multiplier using three distinct architectures: pipeline, wave pipeline, and modified wave pipeline in terms of delay and clock skew. Methods: The 16 × 16 Vedic multiplier was constructed and designed through four numbers of an 8x8 Vedic multiplier. For the 16x16 Vedic multiplier, the 3-stage pipeline and wave pipeline techniques are applied, and the delay performances of the Vedic multiplier are compared. Delay optimization: In the wave pipeline Vedic multiplier architecture, the delay is decreased by inserting the known delay on the longest path delay between the multiplier and adder. Clock skew optimization: The clock skew issue of the wave pipeline Vedic multiplier architecture is minimized by adjusting the setup time violation of the clock signal that is connected to the input and output registers. Findings: The delay performance of the Vedic multiplier was evaluated by the synthesis tools Xilinx 12.1, Xilinx ISE 14.2, and Altera, and based on the synthesis report, the Xilinx synthesis tool offers 73.71% delay performance for the pipeline approach and 53.39% for the wave pipeline approach compared to the Altera tool. Further delay is reduced by the proposed modified wave pipeline approach, which saves 2.122 ns of delay compared to the wave pipeline architecture. The clock skew performance was analyzed using the Time Quest timing analyzer tool, and it was minimized to 0.035 from 0.048 compared to the wave pipeline approach. Novelty: In this work, the modified wave pipeline approach has been applied to the existing Vedic multiplier architecture, and it offers less delay as well as less clock skew compared to the existing method. Hence, the performance of the Vedic multiplier with a modified wave pipelined approach was evaluated through a 3-tap FIR filter by applying a vibroarthrography signal. Keywords: Pipeline, Wave Pipeline, Vedic Multiplier, Clock skew, Set up violation, Altera quartex- II Time quest timing analyzer tool","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"516 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140749950","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}
Objectives: Designing and developing i-PomDiagnoser: a real-time pomegranate disease management system for disease detection, classification, prediction, recommending preventive measures, and analyzing abrupt climatic changes and their impact on pomegranates. Methods: A data collection framework has been designed and developed using an agriculture drone, sensors, camera, and other equipment to collect real field pomegranate images and micro-level parameters. Comprehensive Exploratory Data Analysis (EDA) and Feature Selection (FS) processes were carried out to improve the accuracy of disease classification and forecasting models. ML-based Binary, Multimodel, and Multilabel classifiers were implemented for disease classification. The models were trained on 11 years of historical data and tested on 5 months of actual field data. A hybrid pomegranate disease forecasting model has been developed for accurately forecasting micro-level parameters for the next 45 days to predict diseases. Findings: Micro-level (weather, soil, water) parameters specific to the agro-climatic zone were collected. The five most prominent distinct diseases are considered for experimentation namely Bacterial Blight (Telya), Anthracnose, Fruit spot, Fusarium Wilt, and Fruit borer. The proposed Improved Ensemble Multilabel Classifier (i-Ensemble-MLC) with a modified voting scheme has achieved a high classification accuracy of 95.82%, addressing model overfitting and data imbalance. Moreover, the hybrid pomegranate disease forecasting model, combining LSTM and i-Ensemble-MLC, demonstrated better performance with minimal error rates (MSE: 0.003, RMSE: 0.071, MAE: 0.048, R2: 0.7) compared to the existing model1 (MSE:0.037, MAE:0.028). Novelty: The novelty lies in the creation of the all-in-one model, i-PomDiagnoser. This innovative system helps the farmers to correctly detect and predict the most prominent diseases of pomegranate. Keywords: Pomegranate, Agriculture, Disease Forecasting, Machine Learning, Deep Learning
{"title":"i-PomDiagnoser: A Real-Time Pomegranate Disease Management System","authors":"Vaishali Nirgude, S. Rathi","doi":"10.17485/ijst/v17i14.57","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.57","url":null,"abstract":"Objectives: Designing and developing i-PomDiagnoser: a real-time pomegranate disease management system for disease detection, classification, prediction, recommending preventive measures, and analyzing abrupt climatic changes and their impact on pomegranates. Methods: A data collection framework has been designed and developed using an agriculture drone, sensors, camera, and other equipment to collect real field pomegranate images and micro-level parameters. Comprehensive Exploratory Data Analysis (EDA) and Feature Selection (FS) processes were carried out to improve the accuracy of disease classification and forecasting models. ML-based Binary, Multimodel, and Multilabel classifiers were implemented for disease classification. The models were trained on 11 years of historical data and tested on 5 months of actual field data. A hybrid pomegranate disease forecasting model has been developed for accurately forecasting micro-level parameters for the next 45 days to predict diseases. Findings: Micro-level (weather, soil, water) parameters specific to the agro-climatic zone were collected. The five most prominent distinct diseases are considered for experimentation namely Bacterial Blight (Telya), Anthracnose, Fruit spot, Fusarium Wilt, and Fruit borer. The proposed Improved Ensemble Multilabel Classifier (i-Ensemble-MLC) with a modified voting scheme has achieved a high classification accuracy of 95.82%, addressing model overfitting and data imbalance. Moreover, the hybrid pomegranate disease forecasting model, combining LSTM and i-Ensemble-MLC, demonstrated better performance with minimal error rates (MSE: 0.003, RMSE: 0.071, MAE: 0.048, R2: 0.7) compared to the existing model1 (MSE:0.037, MAE:0.028). Novelty: The novelty lies in the creation of the all-in-one model, i-PomDiagnoser. This innovative system helps the farmers to correctly detect and predict the most prominent diseases of pomegranate. Keywords: Pomegranate, Agriculture, Disease Forecasting, Machine Learning, Deep Learning","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"7 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140747669","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}
Objectives: This article develops the third order Runge-Kutta method, which uses a linear combination of the arithmetic mean, root mean square, and centroidal mean, to solve hybrid fuzzy differential equations. Methods: Seikkala's derivative is taken into account, and a numerical example is provided to show the efficacy of the proposed method. The outcomes demonstrate that the suggested approach is an effective tool for approximating the solution of hybrid fuzzy differential equations. Findings: The comparative analysis was carried out using the third order Runge-Kutta method that is currently in use and is based on arithmetic mean, root mean square, and centroidal mean. Compared to other methods, the suggested method offers a more accurate approximation. Novelty: In this study a new formula has been developed by combining three means Arithmetic Mean, Root Mean Square, and Centroidal Mean using Khattri's formula. And the developed formula is used to solve the third order Runge-Kutta method for the first order hybrid fuzzy differential equation. All real life problems which can be modeled in to an initial value problem can be solved using this formula. Keywords: Hybrid fuzzy differential equations, Triangular fuzzy number, Seikkala's derivative, third order Runge-Kutta method, Arithmetic mean, Root mean square, Centroidal mean, Initial value problem
{"title":"Numerical Solution of Hybrid Fuzzy Differential Equation by using Third Order Runge-Kutta Method Based on Linear Combination of Arithmetic Mean, Root Mean Square and Centroidal Mean","authors":"P. E. D. Rajakumari, R. G. Sharmila","doi":"10.17485/ijst/v17i14.64","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.64","url":null,"abstract":"Objectives: This article develops the third order Runge-Kutta method, which uses a linear combination of the arithmetic mean, root mean square, and centroidal mean, to solve hybrid fuzzy differential equations. Methods: Seikkala's derivative is taken into account, and a numerical example is provided to show the efficacy of the proposed method. The outcomes demonstrate that the suggested approach is an effective tool for approximating the solution of hybrid fuzzy differential equations. Findings: The comparative analysis was carried out using the third order Runge-Kutta method that is currently in use and is based on arithmetic mean, root mean square, and centroidal mean. Compared to other methods, the suggested method offers a more accurate approximation. Novelty: In this study a new formula has been developed by combining three means Arithmetic Mean, Root Mean Square, and Centroidal Mean using Khattri's formula. And the developed formula is used to solve the third order Runge-Kutta method for the first order hybrid fuzzy differential equation. All real life problems which can be modeled in to an initial value problem can be solved using this formula. Keywords: Hybrid fuzzy differential equations, Triangular fuzzy number, Seikkala's derivative, third order Runge-Kutta method, Arithmetic mean, Root mean square, Centroidal mean, Initial value problem","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"383 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140749982","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}
Pub Date : 2024-04-03DOI: 10.17485/ijst/v17i14.3193
Godbless G Minja, D. Nyambo, Anael E Sam
Objectives: This work aims to contribute towards Tanzanian Central Bank Digital Currency (CBDC) users’ privacy preservation. It proposes the design of a privacy preserving CBDC which might be issued by Tanzania's Central Bank (CB), the Bank of Tanzania (BoT), which is currently in CBDC research phase. The work also aims to contribute to literature, the CBDC research being done by BoT, other CBs and CBDC stakeholders around the world. Methods: By using the Design Science Research (DSR) methodology, a privacy preserving CBDC design suitable for Tanzania was proposed, demonstrated and evaluated. This is the result of existing literature showing that different countries have different CBDC designs due to their differences in contexts and purposes for CBDC issuance. This consequently emphasized the fact that a CBDC design should not be treated as a one-size fits all solution. Findings: As opposed to the existing general and other country specific CBDC designs, we proposed a privacy preserving CBDC design suitable for Tanzania by consulting literature and taking into consideration the Tanzanian context. The design appears to be promising Tanzanian CBDC users’ privacy preservation though further work needs to be done. The work should not only be on practical evaluation of the proposed design but also on other factors impacting the success of CBDC projects. This will consequently further increase the success probability of CBDC projects, hence the potential for practical realization of CBDC project benefits. Novelty: Existing literature has shown that, considering the countries’ differences in context and CBDC issuance purposes, CBDC design should not be treated as a generic solution thereby obliging the need for country-specific CBDC designs. Consequently, the privacy preserving CBDC design suitable specifically for Tanzania consists of and provides an outline of privacy preserving interactions among the identified key Tanzanian CBDC participants or actors. The actors are the BoT, the intermediaries (i.e., other banks and payment service providers), Tanzania’s National Identification Authority (NIDA), financial transactions violation detection engine, and the expected CBDC users. Keywords: Digital currency, database privacy, central bank digital currency, privacy
{"title":"Database Privacy: Design of User Privacy Preserving Central Bank Digital Currency: A Case of Tanzania","authors":"Godbless G Minja, D. Nyambo, Anael E Sam","doi":"10.17485/ijst/v17i14.3193","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.3193","url":null,"abstract":"Objectives: This work aims to contribute towards Tanzanian Central Bank Digital Currency (CBDC) users’ privacy preservation. It proposes the design of a privacy preserving CBDC which might be issued by Tanzania's Central Bank (CB), the Bank of Tanzania (BoT), which is currently in CBDC research phase. The work also aims to contribute to literature, the CBDC research being done by BoT, other CBs and CBDC stakeholders around the world. Methods: By using the Design Science Research (DSR) methodology, a privacy preserving CBDC design suitable for Tanzania was proposed, demonstrated and evaluated. This is the result of existing literature showing that different countries have different CBDC designs due to their differences in contexts and purposes for CBDC issuance. This consequently emphasized the fact that a CBDC design should not be treated as a one-size fits all solution. Findings: As opposed to the existing general and other country specific CBDC designs, we proposed a privacy preserving CBDC design suitable for Tanzania by consulting literature and taking into consideration the Tanzanian context. The design appears to be promising Tanzanian CBDC users’ privacy preservation though further work needs to be done. The work should not only be on practical evaluation of the proposed design but also on other factors impacting the success of CBDC projects. This will consequently further increase the success probability of CBDC projects, hence the potential for practical realization of CBDC project benefits. Novelty: Existing literature has shown that, considering the countries’ differences in context and CBDC issuance purposes, CBDC design should not be treated as a generic solution thereby obliging the need for country-specific CBDC designs. Consequently, the privacy preserving CBDC design suitable specifically for Tanzania consists of and provides an outline of privacy preserving interactions among the identified key Tanzanian CBDC participants or actors. The actors are the BoT, the intermediaries (i.e., other banks and payment service providers), Tanzania’s National Identification Authority (NIDA), financial transactions violation detection engine, and the expected CBDC users. Keywords: Digital currency, database privacy, central bank digital currency, privacy","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140748201","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}
Pub Date : 2024-04-03DOI: 10.17485/ijst/v17i14.416
S. J. Arunachalam, R. Saravanan
Objective: The prime goal of this study is to conduct a comprehensive analysis, modelling, and optimization of various independent factors and coming up with a material that suits in structural application in automobile. Method: Composite is prepared using hand lay-up technique. The analysis is carried out through the utilization of the Central Composite Design (CCD) approach. Mathematical models are formulated for ultimate tensile strength and impact resistance, employing the RSM. These factors include fiber orientation, fiber sequence, and filler percentage, with a focus on their influence on mechanical properties. Finding: These models act as valuable tools for the selection of the most favourable independent variables to maximize the mechanical properties related to tensile strength and impact resistance. In conclusion, the experimental findings emphasize that the inclusion of Nano-filler results in an enhancement of 20% and 36% on tensile strength and impact properties respectively. Novelty: TiO2-infused polymers exhibit unparalleled strength and flexibility, promising transformative advancements in this work that can be implemented in aerospace, indoor, automobile, and medical industries. Keywords: Titanium dioxide, Nanofiller, Hybrid composite, Response surface methodology, Epoxy
{"title":"Effect of TiO2 Nano-Filler with Jute/Kenaf/Glass in Tensile and Impact Properties on Fiber Stacking Sequence","authors":"S. J. Arunachalam, R. Saravanan","doi":"10.17485/ijst/v17i14.416","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.416","url":null,"abstract":"Objective: The prime goal of this study is to conduct a comprehensive analysis, modelling, and optimization of various independent factors and coming up with a material that suits in structural application in automobile. Method: Composite is prepared using hand lay-up technique. The analysis is carried out through the utilization of the Central Composite Design (CCD) approach. Mathematical models are formulated for ultimate tensile strength and impact resistance, employing the RSM. These factors include fiber orientation, fiber sequence, and filler percentage, with a focus on their influence on mechanical properties. Finding: These models act as valuable tools for the selection of the most favourable independent variables to maximize the mechanical properties related to tensile strength and impact resistance. In conclusion, the experimental findings emphasize that the inclusion of Nano-filler results in an enhancement of 20% and 36% on tensile strength and impact properties respectively. Novelty: TiO2-infused polymers exhibit unparalleled strength and flexibility, promising transformative advancements in this work that can be implemented in aerospace, indoor, automobile, and medical industries. Keywords: Titanium dioxide, Nanofiller, Hybrid composite, Response surface methodology, Epoxy","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"204 S1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140746779","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}
Pub Date : 2024-03-01DOI: 10.17485/ijst/v17i10.2439
T. S. Mary, B. W. D. Raja
Objective: To determine how a scaffolding-fused digital game impacted primary school students' enjoyment and engagement in Mathematics. Method: This experimental study was carried out with two groups of primary students. The experimental group was taught using the scaffolding fused digital game-based learning, whereas the control group was taught with the conventional method. The instruments used in this study were pre and post-interviews, and, pre and post-observations. The data were analysed using independent t-tests, matched pair t-tests and a One-way Analysis of Covariance. Findings: The results revealed statistically significant differences concerning enjoyment (F = 34.373, P < .05) and engagement (F = 6.498, P < .05) in mathematics learning at 0.01. The enjoyment and engagement of students in the experimental group were much higher than that of the control group. Novelty: As a result of technological advancement, games play an essential role in mathematics education today. Affective factors, precisely emotions, have been widely recognised as influential elements contributing to enjoyment engagement and achievement in the learning process. Engaged learners are motivated, inspired, and eager to put effort into their learning. Keywords: Scaffolding, Enjoyment, Engagemen, Digital game based learning
目的确定融合了支架的数字游戏如何影响小学生对数学的喜爱和参与。研究方法本实验研究以两组小学生为对象。实验组采用支架式融合数字游戏学习法进行教学，而对照组则采用传统方法进行教学。本研究使用的工具包括前后访谈和前后观察。数据分析采用了独立 t 检验、配对 t 检验和单向协方差分析。研究结果结果表明，在 0.01 时，数学学习的乐趣（F = 34.373，P < .05）和参与度（F = 6.498，P < .05）在统计学上存在显著差异。实验组学生的学习乐趣和参与度远远高于对照组。新颖性：随着科技的进步，游戏在当今的数学教育中发挥着至关重要的作用。情感因素，确切地说是情绪，已被广泛认为是促进学习过程中的乐趣和成就的影响因素。参与其中的学习者有动力、有灵感，并渴望在学习中付出努力。关键词脚手架 享受 投入 基于数字游戏的学习
{"title":"Optimising Students’ Enjoyment and Engagement in Learning via Scaffolding-fused Digital Game-based Learning","authors":"T. S. Mary, B. W. D. Raja","doi":"10.17485/ijst/v17i10.2439","DOIUrl":"https://doi.org/10.17485/ijst/v17i10.2439","url":null,"abstract":"Objective: To determine how a scaffolding-fused digital game impacted primary school students' enjoyment and engagement in Mathematics. Method: This experimental study was carried out with two groups of primary students. The experimental group was taught using the scaffolding fused digital game-based learning, whereas the control group was taught with the conventional method. The instruments used in this study were pre and post-interviews, and, pre and post-observations. The data were analysed using independent t-tests, matched pair t-tests and a One-way Analysis of Covariance. Findings: The results revealed statistically significant differences concerning enjoyment (F = 34.373, P < .05) and engagement (F = 6.498, P < .05) in mathematics learning at 0.01. The enjoyment and engagement of students in the experimental group were much higher than that of the control group. Novelty: As a result of technological advancement, games play an essential role in mathematics education today. Affective factors, precisely emotions, have been widely recognised as influential elements contributing to enjoyment engagement and achievement in the learning process. Engaged learners are motivated, inspired, and eager to put effort into their learning. Keywords: Scaffolding, Enjoyment, Engagemen, Digital game based learning","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"18 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140086484","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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