Pub Date : 2024-04-16DOI: 10.17485/ijst/v17i15.3016
Tsegaye Amare, Balkeshwar Singh, Guteta Kabeta, M. Jiru, H. Lemu
Objectives: The challenges of implementing a lean business system can be solved by Structural Equation Modeling. In this research, the link between lean operational, financial performance, and customer satisfaction has been investigated in the Akaki Basic Metal Industry in Ethiopia. Methods: A lean operational performance that met the needs of the industry was identified by conducting a structural survey questionnaire to collect feedback data from experts. The model was developed including 28 variables from the experts in the industry. The collected responses were tested for reliability and validity using Cronbach's alpha, composite reliability, convergent, and discriminant validity. Findings: From the use of Analysis of Moments and Structures (AMOS-SEM), the results confirmed that C.R. > 1.96, p < 0.001, and p < 0.05 on quality and delivery. This shows a significant positive direct effect on customer satisfaction by 25.8% on quality, 24.9% on delivery, and 10.3% on cost. Novelty: Even though LM has become a fundamental aspect of industrial manufacturing processes, lack of understanding (knowledge) and practicing how to implement the positive impact on lean operational, financial performance, and customer satisfaction are still not sufficiently exploited particularly in developing countries. This research adds values to the practical use of the concept by examining the relationship among lean operational, financial performance, and customer satisfaction within basic metal manufacturing industry in Ethiopia. In addition to this, the findings have demonstrated improved organizational performance through structural equation modeling. It also helps leaders to focus more on training employees on quality issues and developing an awareness of quality achievement as a core value in the industry. Keywords: Confirmatory factor analysis, Exploratory factor analysis, Lean operational performance, Structural equation modeling, Customer satisfaction
{"title":"Structural Equation Modeling of Relationships Among Lean Operational, Financial Performance, and Customer Satisfaction","authors":"Tsegaye Amare, Balkeshwar Singh, Guteta Kabeta, M. Jiru, H. Lemu","doi":"10.17485/ijst/v17i15.3016","DOIUrl":"https://doi.org/10.17485/ijst/v17i15.3016","url":null,"abstract":"Objectives: The challenges of implementing a lean business system can be solved by Structural Equation Modeling. In this research, the link between lean operational, financial performance, and customer satisfaction has been investigated in the Akaki Basic Metal Industry in Ethiopia. Methods: A lean operational performance that met the needs of the industry was identified by conducting a structural survey questionnaire to collect feedback data from experts. The model was developed including 28 variables from the experts in the industry. The collected responses were tested for reliability and validity using Cronbach's alpha, composite reliability, convergent, and discriminant validity. Findings: From the use of Analysis of Moments and Structures (AMOS-SEM), the results confirmed that C.R. > 1.96, p < 0.001, and p < 0.05 on quality and delivery. This shows a significant positive direct effect on customer satisfaction by 25.8% on quality, 24.9% on delivery, and 10.3% on cost. Novelty: Even though LM has become a fundamental aspect of industrial manufacturing processes, lack of understanding (knowledge) and practicing how to implement the positive impact on lean operational, financial performance, and customer satisfaction are still not sufficiently exploited particularly in developing countries. This research adds values to the practical use of the concept by examining the relationship among lean operational, financial performance, and customer satisfaction within basic metal manufacturing industry in Ethiopia. In addition to this, the findings have demonstrated improved organizational performance through structural equation modeling. It also helps leaders to focus more on training employees on quality issues and developing an awareness of quality achievement as a core value in the industry. Keywords: Confirmatory factor analysis, Exploratory factor analysis, Lean operational performance, Structural equation modeling, Customer satisfaction","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140698819","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 : 2024-04-16DOI: 10.17485/ijst/v17i15.368
V. N. Ganesh, N. Divyah, R. Rajkumar
Objectives: The goal of this project is to better understand the interaction between fibers and concrete in order to produce Light Weight Aggregate Concrete (LWAC) with improved structural performance that is made from recycled materials, such as sintered flyash aggregate, and LWAC structures that are more resistant to impact loads and other dynamic forces. Methods: The sintered flyash aggregates are added as coarse aggregate to the concrete and basalt fiber (0.25% of mix) is used as a secondary reinforcement to improve the energy absorption, impact resistance and toughness behaviour. M30 grade of concrete was arrived after laboratory trials after which the mechanical properties were evaluated. The effect of drop impact load on slabs of size 300mm x 300mm x 50mm reinforced with two layers of bundled wire mesh was studied. The flexural properties of concrete reinforced with fiber prism of size 500mm x 100mm x 100mm were evaluated. Findings: With the addition of fiber, flexural toughness index and post-cracking toughness were increased notably on the initial deflections and cracks. The conventional fiber reinforced concrete exhibited a superior peak load capacity compared to normal weight concrete, with a measured increase of 7.5%. Conversely, normal-weight concrete demonstrated a significantly higher deflection under load, exceeding that of fiber reinforced concrete by 47%. LWAC displayed a distinct increase in both peak load (18.7%) and deflection (39.13%) when compared to Normal Weight Aggregate Concrete (NWAC). The incorporation of basalt fiber enhanced the energy absorption by 150% in NWAC and 80% in LWAC. Novelty: The incorporation of fiber into lightweight concrete reduces the brittle nature of failure. The post-cracking toughness behaviour was enhanced because of the effect of crack-arresting by fibers. After the first break, it was discovered to retain residual strength, and removing the fibers from the matrix required more force. Keywords: Sintered flyash aggregate, Light weight concrete, Basalt fiber, Toughness, Impact load, Energy absorption
目标：本项目的目标是更好地了解纤维与混凝土之间的相互作用，以便生产出结构性能更佳的轻质骨料混凝土（LWAC），这种混凝土由烧结粉煤灰骨料等回收材料制成，而且轻质骨料混凝土结构更能抵抗冲击荷载和其他动态力。方法：将烧结粉煤灰骨料作为粗骨料添加到混凝土中，并使用玄武岩纤维（占混合料的 0.25%）作为辅助加固材料，以改善能量吸收、抗冲击和韧性性能。经过实验室试验后，获得了 M30 级混凝土，并对其力学性能进行了评估。研究了跌落冲击荷载对使用两层捆扎金属丝网加固的 300mm x 300mm x 50mm 板的影响。评估了用 500mm x 100mm x 100mm 大小的纤维棱柱加固的混凝土的抗弯特性。研究结果添加纤维后，在初始挠度和裂缝处的韧度指数和开裂后韧度显著增加。与正常重量的混凝土相比，传统纤维增强混凝土的峰值承载能力更强，测量结果提高了 7.5%。相反，正常重量混凝土在荷载作用下的挠度明显增大，比纤维增强混凝土高出 47%。与正常重量骨料混凝土（NWAC）相比，LWAC 的峰值荷载（18.7%）和挠度（39.13%）都有明显增加。加入玄武岩纤维后，NWAC 的能量吸收能力提高了 150%，LWAC 的能量吸收能力提高了 80%。新颖性：在轻质混凝土中掺入纤维可降低破坏时的脆性。由于纤维的抗裂作用，开裂后的韧性得到了增强。在第一次断裂后，发现纤维保留了残余强度，从基体中去除纤维需要更大的力。关键词烧结粉煤灰骨料 轻质混凝土 玄武岩纤维 韧性 冲击荷载 能量吸收
{"title":"Enhancing Structural Performance: Fiber Reinforcement in Sintered Flyash Lightweight Concrete for Impact Resistance and Toughness","authors":"V. N. Ganesh, N. Divyah, R. Rajkumar","doi":"10.17485/ijst/v17i15.368","DOIUrl":"https://doi.org/10.17485/ijst/v17i15.368","url":null,"abstract":"Objectives: The goal of this project is to better understand the interaction between fibers and concrete in order to produce Light Weight Aggregate Concrete (LWAC) with improved structural performance that is made from recycled materials, such as sintered flyash aggregate, and LWAC structures that are more resistant to impact loads and other dynamic forces. Methods: The sintered flyash aggregates are added as coarse aggregate to the concrete and basalt fiber (0.25% of mix) is used as a secondary reinforcement to improve the energy absorption, impact resistance and toughness behaviour. M30 grade of concrete was arrived after laboratory trials after which the mechanical properties were evaluated. The effect of drop impact load on slabs of size 300mm x 300mm x 50mm reinforced with two layers of bundled wire mesh was studied. The flexural properties of concrete reinforced with fiber prism of size 500mm x 100mm x 100mm were evaluated. Findings: With the addition of fiber, flexural toughness index and post-cracking toughness were increased notably on the initial deflections and cracks. The conventional fiber reinforced concrete exhibited a superior peak load capacity compared to normal weight concrete, with a measured increase of 7.5%. Conversely, normal-weight concrete demonstrated a significantly higher deflection under load, exceeding that of fiber reinforced concrete by 47%. LWAC displayed a distinct increase in both peak load (18.7%) and deflection (39.13%) when compared to Normal Weight Aggregate Concrete (NWAC). The incorporation of basalt fiber enhanced the energy absorption by 150% in NWAC and 80% in LWAC. Novelty: The incorporation of fiber into lightweight concrete reduces the brittle nature of failure. The post-cracking toughness behaviour was enhanced because of the effect of crack-arresting by fibers. After the first break, it was discovered to retain residual strength, and removing the fibers from the matrix required more force. Keywords: Sintered flyash aggregate, Light weight concrete, Basalt fiber, Toughness, Impact load, Energy absorption","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"28 S87","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140695288","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 : 2024-04-16DOI: 10.17485/ijst/v17i15.322
G. Rajkumar, K. Somaiah, K. Narasimharao, B. Venkateswararao
Objective: The objective of this article is to derive the dispersion relations of elastic waves along a cylindrical rod of homogeneous, isotropic micropolar elastic solid with stretch under impedance boundary conditions. Method: The basic equations and constitutive relations are converted into cylindrical coordinates and solved by adopting the method of plane harmonic solution. Findings: Displacements, micro rotations, and micro stretch relations are derived analytically. The dispersion relations pertaining to elastic waves with using impedance boundary conditions also derived analytically and these relations are compared with the results of Tomar. Novelty: With the use of the MATLAB program, the effects of impedance parameters, micropolarity and stretch are discussed for a particular model. The speed of the elastic wave is proportional to the ratio of the impedance parameter in microstretch elastic solids, but there is no significant effect of the impedance ratio in micropolar elastic solids. Keywords: Elastic Waves, Cylindrical rod, Micropolarity, Micro stretch, Impedance Boundary Conditions
{"title":"Propagation of Elastic Waves along a Cylindrical Rod of Micropolar Elastic Solid with Stretch under Impedance Boundary Conditions","authors":"G. Rajkumar, K. Somaiah, K. Narasimharao, B. Venkateswararao","doi":"10.17485/ijst/v17i15.322","DOIUrl":"https://doi.org/10.17485/ijst/v17i15.322","url":null,"abstract":"Objective: The objective of this article is to derive the dispersion relations of elastic waves along a cylindrical rod of homogeneous, isotropic micropolar elastic solid with stretch under impedance boundary conditions. Method: The basic equations and constitutive relations are converted into cylindrical coordinates and solved by adopting the method of plane harmonic solution. Findings: Displacements, micro rotations, and micro stretch relations are derived analytically. The dispersion relations pertaining to elastic waves with using impedance boundary conditions also derived analytically and these relations are compared with the results of Tomar. Novelty: With the use of the MATLAB program, the effects of impedance parameters, micropolarity and stretch are discussed for a particular model. The speed of the elastic wave is proportional to the ratio of the impedance parameter in microstretch elastic solids, but there is no significant effect of the impedance ratio in micropolar elastic solids. Keywords: Elastic Waves, Cylindrical rod, Micropolarity, Micro stretch, Impedance Boundary Conditions","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140698822","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 : 2024-04-16DOI: 10.17485/ijst/v17i15.765
G. Shimi, C. J. Mahibha, Durairaj Thenmozhi
Objectives: Language detection is the process of identifying a language associated with a text. The proposed system aims to detect the Dravidian language that is associated with the given text using different machine learning and deep learning algorithms. The paper presents an empirical analysis of the results obtained using the different models. It also aims to evaluate the performance of a language agnostic model for the purpose of language detection. Method: An empirical analysis of Dravidian language identification in social media text using machine learning and deep learning approaches with k-fold cross validation has been implemented. The identification of Dravidian languages, including Tamil, Malayalam, Tamil Code Mix, and Malayalam Code Mix, is performed using both machine learning (ML) and deep learning algorithms. The machine learning algorithms used for language detection are Naive Bayes (NB), Multinomial Logistic Regression (MLR), Support Vector Machine (SVM), and Random Forest (RF). The supervised Deep Learning (DL) models used include BERT, mBERT and language agnostic models. Findings: The language agnostic model outperform all other models considering the task of language detection in Dravidian languages. The results of both the ML and DL models are analyzed empirically with performance measures like accuracy, precision, recall, and f1-score. The accuracy associated with different machine learning algorithms varies from 85% to 89%. It is evident from the experimental result that the deep learning model outperformed with an accuracy of 98%. Novelty: The proposed system emphasizes on the use of the language agnostic model to implement the process of detecting Dravidian languages associated with the given text which provides a promising result of 98% accuracy which is higher than the existing methodologies. Keywords: Language, Machine learning, Deep learning, Transformer model, Encoder, Decoder
目标语言检测是识别与文本相关的语言的过程。所提议的系统旨在使用不同的机器学习和深度学习算法来检测与给定文本相关的德拉威语。本文对使用不同模型获得的结果进行了实证分析。本文还旨在评估一种语言无关模型在语言检测方面的性能。方法使用机器学习和深度学习方法，通过 k 倍交叉验证，对社交媒体文本中的德拉维德语进行了实证分析。使用机器学习（ML）和深度学习算法识别德拉威语，包括泰米尔语、马拉雅拉姆语、泰米尔语代码混合和马拉雅拉姆语代码混合。用于语言检测的机器学习算法有：Naive Bayes (NB)、Multinomial Logistic Regression (MLR)、Support Vector Machine (SVM) 和 Random Forest (RF)。使用的深度学习（DL）监督模型包括 BERT、mBERT 和语言无关模型。研究结果考虑到 Dravidian 语言的语言检测任务，语言不可知论模型优于所有其他模型。我们通过准确率、精确度、召回率和 f1 分数等性能指标对 ML 和 DL 模型的结果进行了实证分析。不同机器学习算法的准确率从 85% 到 89% 不等。从实验结果可以看出，深度学习模型的准确率高达 98%，表现更胜一筹。新颖性：所提出的系统强调使用语言不可知论模型来实现检测与给定文本相关的德拉维德语言的过程，其准确率达到 98%，高于现有方法，结果令人鼓舞。关键词语言 机器学习 深度学习 变换器模型 编码器 解码器
{"title":"An Empirical Analysis of Language Detection in Dravidian Languages","authors":"G. Shimi, C. J. Mahibha, Durairaj Thenmozhi","doi":"10.17485/ijst/v17i15.765","DOIUrl":"https://doi.org/10.17485/ijst/v17i15.765","url":null,"abstract":"Objectives: Language detection is the process of identifying a language associated with a text. The proposed system aims to detect the Dravidian language that is associated with the given text using different machine learning and deep learning algorithms. The paper presents an empirical analysis of the results obtained using the different models. It also aims to evaluate the performance of a language agnostic model for the purpose of language detection. Method: An empirical analysis of Dravidian language identification in social media text using machine learning and deep learning approaches with k-fold cross validation has been implemented. The identification of Dravidian languages, including Tamil, Malayalam, Tamil Code Mix, and Malayalam Code Mix, is performed using both machine learning (ML) and deep learning algorithms. The machine learning algorithms used for language detection are Naive Bayes (NB), Multinomial Logistic Regression (MLR), Support Vector Machine (SVM), and Random Forest (RF). The supervised Deep Learning (DL) models used include BERT, mBERT and language agnostic models. Findings: The language agnostic model outperform all other models considering the task of language detection in Dravidian languages. The results of both the ML and DL models are analyzed empirically with performance measures like accuracy, precision, recall, and f1-score. The accuracy associated with different machine learning algorithms varies from 85% to 89%. It is evident from the experimental result that the deep learning model outperformed with an accuracy of 98%. Novelty: The proposed system emphasizes on the use of the language agnostic model to implement the process of detecting Dravidian languages associated with the given text which provides a promising result of 98% accuracy which is higher than the existing methodologies. Keywords: Language, Machine learning, Deep learning, Transformer model, Encoder, Decoder","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"24 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140696657","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 : 2024-04-16DOI: 10.17485/ijst/v17i15.3044
A. Abirami, S. Lakshmanaprakash, R. L. Priya, Vaishali Hirlekar, Bhargavi Dalal
Objectives: This study objective is to create a proactive forensic framework with a classification model to identify the malicious content to avoid cyber-attacks. Methods: In this proposed work, a novel framework is introduced to analyze and detect network attacks before it happens. It monitors the network packet flow, captures the packets, analyzes the packet flow proactively, and detects cyber-attacks using different machine learning algorithms and Deep Convolution Neural network (CNN) technique. The KDD dataset is used in this experiment with 30% for testing and 80% for training. Findings: The simulation results show that the detection percentage of the proposed framework reaches a maximum of 95.92% in different scenarios. It is approximately 10% higher than the existing proactive frameworks for example Gawand’s model, Ahmetoglu’s model and many more. Novelty and applications: The proposed framework is a proactive model which detects the cyber-attack in prior to avoid cyber-attacks. The deep CNN model highly efficient for detecting cyber-attack. Keywords: Proactive Forensic Framework, Deep CNN, Classification Algorithms, Cyber attack detection, Intrusion Detection System
{"title":"Proactive Analysis and Detection of Cyber-attacks using Deep Learning Techniques","authors":"A. Abirami, S. Lakshmanaprakash, R. L. Priya, Vaishali Hirlekar, Bhargavi Dalal","doi":"10.17485/ijst/v17i15.3044","DOIUrl":"https://doi.org/10.17485/ijst/v17i15.3044","url":null,"abstract":"Objectives: This study objective is to create a proactive forensic framework with a classification model to identify the malicious content to avoid cyber-attacks. Methods: In this proposed work, a novel framework is introduced to analyze and detect network attacks before it happens. It monitors the network packet flow, captures the packets, analyzes the packet flow proactively, and detects cyber-attacks using different machine learning algorithms and Deep Convolution Neural network (CNN) technique. The KDD dataset is used in this experiment with 30% for testing and 80% for training. Findings: The simulation results show that the detection percentage of the proposed framework reaches a maximum of 95.92% in different scenarios. It is approximately 10% higher than the existing proactive frameworks for example Gawand’s model, Ahmetoglu’s model and many more. Novelty and applications: The proposed framework is a proactive model which detects the cyber-attack in prior to avoid cyber-attacks. The deep CNN model highly efficient for detecting cyber-attack. Keywords: Proactive Forensic Framework, Deep CNN, Classification Algorithms, Cyber attack detection, Intrusion Detection System","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"57 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140694587","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 : 2024-04-16DOI: 10.17485/ijst/v17i15.456
M. Dhanushree, R. Priya, P. Aruna, R. Bhavani
Objectives: To develop an efficient Video Summarization technique that aims to utilize the saliency map for mimicking the human way of selecting the important events in the given video. Methods: This paper proposes Histogram based Weighted Fusion (HWF) algorithm that uses spatial and temporal saliency maps to act as guidance in creating the summary of the video. The spatial saliency score and temporal saliency score obtained from the corresponding saliency maps are fused using the proposed HWF algorithm to obtain the frame level importance score. It tries to depict the visual attention of the human brain when watching a particular video. Findings: The experimental results show that the proposed HWF algorithm performs better than the state-of-the-art methods. Novelty: The use of Histogram intersection and the incorporation of the exponential function as the weight for the combined feature enhance the summarization ability of the proposed model. Keywords: Video Summarization, Saliency Map, Histogram intersection, Contrast sensitivity function, Attention curves
{"title":"A Framework for Video Summarization using Visual Attention Technique","authors":"M. Dhanushree, R. Priya, P. Aruna, R. Bhavani","doi":"10.17485/ijst/v17i15.456","DOIUrl":"https://doi.org/10.17485/ijst/v17i15.456","url":null,"abstract":"Objectives: To develop an efficient Video Summarization technique that aims to utilize the saliency map for mimicking the human way of selecting the important events in the given video. Methods: This paper proposes Histogram based Weighted Fusion (HWF) algorithm that uses spatial and temporal saliency maps to act as guidance in creating the summary of the video. The spatial saliency score and temporal saliency score obtained from the corresponding saliency maps are fused using the proposed HWF algorithm to obtain the frame level importance score. It tries to depict the visual attention of the human brain when watching a particular video. Findings: The experimental results show that the proposed HWF algorithm performs better than the state-of-the-art methods. Novelty: The use of Histogram intersection and the incorporation of the exponential function as the weight for the combined feature enhance the summarization ability of the proposed model. Keywords: Video Summarization, Saliency Map, Histogram intersection, Contrast sensitivity function, Attention curves","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"33 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140696834","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 : 2024-04-16DOI: 10.17485/ijst/v17i15.2495
Nagarani Nagarajan, S. Jothiraj
Objective: To provide a novel approach for automatic Unmanned Aerial Vehicle (UAV) runway detection, leveraging remote sensing data and advanced image processing techniques. Methods: The methodology encompasses Gaussian filter-based despeckling and histogram equalization for preprocessing, followed by Independent Component Analysis (ICA) for feature extraction and segmentation using the K-means clustering algorithm. Findings: The research demonstrates successful UAV runway detection, even with unlabeled datasets, underscoring the efficacy of the proposed methods. Notably, the study contributes to automatic target recognition, specifically in Synthetic Aperture Radar (SAR) data analysis, where K-means clustering outperforms Korn B and morphological algorithms. Novelty : The K-means algorithms works by clustering the datasets obtained by integrating all the data collected from various sensors that are placed at specific positions in the runway. This work holds significance in facilitating immediate runway identification during emergencies and finds applications in military operations, surveillance, and remote sensing domains. Keywords: Runway detection, Unmanned Aerial Vehicle, Histogram Equalization, Gaussian filtering, Independent Component Analysis, K-means clustering based segmentation
目的利用遥感数据和先进的图像处理技术，为无人驾驶飞行器（UAV）跑道自动检测提供一种新方法。方法：该方法包括基于高斯滤波器的去斑和直方图均衡化预处理，然后使用独立分量分析（ICA）进行特征提取，并使用 K-means 聚类算法进行分割。研究结果研究表明，即使在无标注数据集的情况下，也能成功进行无人机跑道检测，这凸显了所提方法的功效。值得注意的是，该研究有助于自动目标识别，特别是在合成孔径雷达（SAR）数据分析中，K均值聚类算法优于 Korn B 算法和形态学算法。新颖性：K-means 算法的工作原理是对从放置在跑道特定位置的各种传感器收集到的所有数据集进行聚类。这项工作有助于在紧急情况下立即识别跑道，并可应用于军事行动、监控和遥感领域。关键词跑道检测、无人机、直方图均衡化、高斯滤波、独立分量分析、基于 K-means 聚类的分割
{"title":"An Innovative Runway Landing Path Detection using UAV Implementation of the K-Means Clustering Algorithm","authors":"Nagarani Nagarajan, S. Jothiraj","doi":"10.17485/ijst/v17i15.2495","DOIUrl":"https://doi.org/10.17485/ijst/v17i15.2495","url":null,"abstract":"Objective: To provide a novel approach for automatic Unmanned Aerial Vehicle (UAV) runway detection, leveraging remote sensing data and advanced image processing techniques. Methods: The methodology encompasses Gaussian filter-based despeckling and histogram equalization for preprocessing, followed by Independent Component Analysis (ICA) for feature extraction and segmentation using the K-means clustering algorithm. Findings: The research demonstrates successful UAV runway detection, even with unlabeled datasets, underscoring the efficacy of the proposed methods. Notably, the study contributes to automatic target recognition, specifically in Synthetic Aperture Radar (SAR) data analysis, where K-means clustering outperforms Korn B and morphological algorithms. Novelty : The K-means algorithms works by clustering the datasets obtained by integrating all the data collected from various sensors that are placed at specific positions in the runway. This work holds significance in facilitating immediate runway identification during emergencies and finds applications in military operations, surveillance, and remote sensing domains. Keywords: Runway detection, Unmanned Aerial Vehicle, Histogram Equalization, Gaussian filtering, Independent Component Analysis, K-means clustering based segmentation","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"7 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697720","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 study aims to enhance cellular manufacturing systems by optimizing cobot and tool assignments, maximizing flexibility, and minimizing production time, workload imbalances, energy consumption, error rates and rework. Methods: This study employs a sophisticated multi-objective optimization approach, integrating constraints into the cellular manufacturing system using advanced linear or integer programming techniques. The model is designed to dynamically adapt in real-time, allowing for flexibility in response to evolving production needs. We systematically evaluate cobot and tool assignments, balancing conflicting objectives within a comprehensive mathematical framework. The optimization process is fine-tuned to consider machine capacities, part type assignments, and tool compatibility, ensuring the practicality and realism of the proposed solutions. The overarching goal is to identify optimal configurations that minimize production time, workload imbalances, energy consumption, error rates and rework while maximizing system adaptability. Findings: The optimal cobot and tool assignments, determined through the multi-objective optimization model, yielded substantial improvements across critical metrics compared to a scenario without cobots. This data showcases a 26% reduction in production time, a 20% decrease in workload imbalance, a 20% improvement in flexibility, a 28% reduction in energy consumption, and a 26% decrease in error rates and rework when utilizing the proposed multi-objective optimization approach. These tangible improvements underscore the practical benefits of integrating cobots in cellular manufacturing systems.Top of Form Novelty: This study introduces a novel multi-objective optimization approach for cellular manufacturing, enhancing adaptability and efficiency through strategic cobot and tool assignments. Keywords: Cellular Manufacturing Systems, Cobots, Tool Assignment, MultiObjective Optimization, Production Time, Workload Balancing, Energy Consumption, Error Rates, Flexibility
{"title":"Optimizing Cellular Manufacturing Systems Through Multi-Objective Cobot Coordination and Tool Allocation","authors":"S. M. Saleemuddin, Sanjeev Reddy K Hudgikar","doi":"10.17485/ijst/v17i14.72","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.72","url":null,"abstract":"Objectives: This study aims to enhance cellular manufacturing systems by optimizing cobot and tool assignments, maximizing flexibility, and minimizing production time, workload imbalances, energy consumption, error rates and rework. Methods: This study employs a sophisticated multi-objective optimization approach, integrating constraints into the cellular manufacturing system using advanced linear or integer programming techniques. The model is designed to dynamically adapt in real-time, allowing for flexibility in response to evolving production needs. We systematically evaluate cobot and tool assignments, balancing conflicting objectives within a comprehensive mathematical framework. The optimization process is fine-tuned to consider machine capacities, part type assignments, and tool compatibility, ensuring the practicality and realism of the proposed solutions. The overarching goal is to identify optimal configurations that minimize production time, workload imbalances, energy consumption, error rates and rework while maximizing system adaptability. Findings: The optimal cobot and tool assignments, determined through the multi-objective optimization model, yielded substantial improvements across critical metrics compared to a scenario without cobots. This data showcases a 26% reduction in production time, a 20% decrease in workload imbalance, a 20% improvement in flexibility, a 28% reduction in energy consumption, and a 26% decrease in error rates and rework when utilizing the proposed multi-objective optimization approach. These tangible improvements underscore the practical benefits of integrating cobots in cellular manufacturing systems.Top of Form Novelty: This study introduces a novel multi-objective optimization approach for cellular manufacturing, enhancing adaptability and efficiency through strategic cobot and tool assignments. Keywords: Cellular Manufacturing Systems, Cobots, Tool Assignment, MultiObjective Optimization, Production Time, Workload Balancing, Energy Consumption, Error Rates, Flexibility","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"2 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140748197","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/v17i14.251
S. P. Subhapriya, M. Thiagarajan
Objectives: Rather than working nonstop in the service area, servers take vacations when they have no clients. To determine the probability and features of the queuing system, this study introduces controllable arrival rates and interdependency in the system's service and arrival processes. It also performs a numerical verification of the results. Methods: A recursive method is employed to solve the steady-state probability equations, yielding explicit iterative formulas under the assumption that a single server provides services to all clients. Here, customer arrivals are controlled as either faster or slower, with Poisson assumed by default. Findings: For this model, steady-state solutions and characteristics are derived and explored, and some numerical analysis is carried out using MATLAB. All the probabilities are expressed in terms of , which indicates the system when empty. The movement of the average number of customers in the system and the expected waiting time, and respectively, of the customers in the system is investigated through a graph. and decrease when dependence service rate, and faster arrival rate increase. Additionally, increases and decreases when the slower arrival rate increases. Novelty: Although there have been studies on vacation in queuing theory, this new approach aims to bridge the gap between vacation and interdependency in the arrival and service process, as well as controllable arrival rates. When vacations with predictable arrival rates are utilised advantageously for the benefit of both the server and the client, waiting times may be minimised and the most practical, economical service can be provided. Keywords: Markovian Queuing System, Vacation, Loss and Delay, Finite Capacity, Interdependent Arrival and Service Rates, Varying Arrival Rates, Bivariate Poisson Process
{"title":"M/M/1 Interdependent Queuing Model with Vacation and Controllable Arrival Rates","authors":"S. P. Subhapriya, M. Thiagarajan","doi":"10.17485/ijst/v17i14.251","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.251","url":null,"abstract":"Objectives: Rather than working nonstop in the service area, servers take vacations when they have no clients. To determine the probability and features of the queuing system, this study introduces controllable arrival rates and interdependency in the system's service and arrival processes. It also performs a numerical verification of the results. Methods: A recursive method is employed to solve the steady-state probability equations, yielding explicit iterative formulas under the assumption that a single server provides services to all clients. Here, customer arrivals are controlled as either faster or slower, with Poisson assumed by default. Findings: For this model, steady-state solutions and characteristics are derived and explored, and some numerical analysis is carried out using MATLAB. All the probabilities are expressed in terms of , which indicates the system when empty. The movement of the average number of customers in the system and the expected waiting time, and respectively, of the customers in the system is investigated through a graph. and decrease when dependence service rate, and faster arrival rate increase. Additionally, increases and decreases when the slower arrival rate increases. Novelty: Although there have been studies on vacation in queuing theory, this new approach aims to bridge the gap between vacation and interdependency in the arrival and service process, as well as controllable arrival rates. When vacations with predictable arrival rates are utilised advantageously for the benefit of both the server and the client, waiting times may be minimised and the most practical, economical service can be provided. Keywords: Markovian Queuing System, Vacation, Loss and Delay, Finite Capacity, Interdependent Arrival and Service Rates, Varying Arrival Rates, Bivariate Poisson Process","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"268 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140750194","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/v17i14.187
G. B. Sathishkumar, B. Asaithambi, V. Srinivasan
Objective: To examine the tribological and mechanical characteristics of the AZ61 alloy reinforced with Stelcar alloy powder by surface modification through laser cladding. Methods: Surface modification was done by using a laser cladding machine, where the input parameters including Scanning Speed (SS), Laser Power (LP) and Powder Feed Rate (PFR) were adjusted. Experimental design followed a L9 Taguchi approach, and optimization of input parameters for the surface modified AZ61 alloy reinforced with Stelcar alloy particles was achieved using Grey Relational Analysis (GRA). Output responses, namely wear volume and micro hardness were measured to assess the effectiveness of the optimization process. Findings: From the results obtained through the experiments, powder feed rate contributes to 82.81% of the variability in wear volume, whereas the laser power mostly impacts micro hardness; influencing it by 89.46% confirmed with ANOVA. In order to determine the optimal processing parameters among various objectives, this research applies the grey relational method. The results showed that the wear volume and micro hardness of the composite were significantly affected by the Stelcar reinforcement. Employing Grey relational analysis combined with several optimization objectives into a transparent method, resulting in a clad material with the lower wear volume and higher micro hardness. The optimized processing parameters predicted grey relational grades with an error rate of 1.39% and a significant contribution of 63.60% from laser power. This study confirmed that multi-objective optimization could enhance laser-cladded surface mechanical characteristics and laid out the theoretical foundation for this approach. Novelty: This study introduces an innovative approach to surface modification by employing the laser cladding technique to reinforce Stelcar alloy particles, thereby creating a dense coating on the substrate. Keywords: Laser Cladding, AZ61 magnesium alloy, Stelcar alloy, Coating, Optimization
{"title":"Surface modification of AZ61 Magnesium Alloy with Stelcar Alloy Powder Using Laser Cladding Technique","authors":"G. B. Sathishkumar, B. Asaithambi, V. Srinivasan","doi":"10.17485/ijst/v17i14.187","DOIUrl":"https://doi.org/10.17485/ijst/v17i14.187","url":null,"abstract":"Objective: To examine the tribological and mechanical characteristics of the AZ61 alloy reinforced with Stelcar alloy powder by surface modification through laser cladding. Methods: Surface modification was done by using a laser cladding machine, where the input parameters including Scanning Speed (SS), Laser Power (LP) and Powder Feed Rate (PFR) were adjusted. Experimental design followed a L9 Taguchi approach, and optimization of input parameters for the surface modified AZ61 alloy reinforced with Stelcar alloy particles was achieved using Grey Relational Analysis (GRA). Output responses, namely wear volume and micro hardness were measured to assess the effectiveness of the optimization process. Findings: From the results obtained through the experiments, powder feed rate contributes to 82.81% of the variability in wear volume, whereas the laser power mostly impacts micro hardness; influencing it by 89.46% confirmed with ANOVA. In order to determine the optimal processing parameters among various objectives, this research applies the grey relational method. The results showed that the wear volume and micro hardness of the composite were significantly affected by the Stelcar reinforcement. Employing Grey relational analysis combined with several optimization objectives into a transparent method, resulting in a clad material with the lower wear volume and higher micro hardness. The optimized processing parameters predicted grey relational grades with an error rate of 1.39% and a significant contribution of 63.60% from laser power. This study confirmed that multi-objective optimization could enhance laser-cladded surface mechanical characteristics and laid out the theoretical foundation for this approach. Novelty: This study introduces an innovative approach to surface modification by employing the laser cladding technique to reinforce Stelcar alloy particles, thereby creating a dense coating on the substrate. Keywords: Laser Cladding, AZ61 magnesium alloy, Stelcar alloy, Coating, Optimization","PeriodicalId":13296,"journal":{"name":"Indian journal of science and technology","volume":"160 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140748502","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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