Leadership decision-making is important for the successful functioning of organizations, so it is necessary for leaders to understand the factors that impact their decisions. Decision-making is always the responsibility of the leader, but in a changing world, it becomes an even more crucial factor for success. Making good decisions requires time, experience, and thorough problem-solving skills. In my research, through the analysis of scholarly sources, I have identified several role factors that clearly influence the decision-making process and its implementation. Furthermore, I have developed a self-designed questionnaire to examine the decision-making role in modern organizations. I analyzed the data from 230 respondents using various statistical methods. Based on my findings, conflict management, risk-taking, and a thorough understanding of the problem strongly determine leadership decision-making processes. The ability of leaders to effectively manage conflicts significantly impacts their decisions. Risk-taking is also of key importance, as leaders need to recognize the risks associated with a given situation and make decisions accordingly.
{"title":"Transformation of the Decisional Leadership Role","authors":"Erik Márta","doi":"10.21791/ijems.2023.035","DOIUrl":"https://doi.org/10.21791/ijems.2023.035","url":null,"abstract":"Leadership decision-making is important for the successful functioning of organizations, so it is necessary for leaders to understand the factors that impact their decisions. Decision-making is always the responsibility of the leader, but in a changing world, it becomes an even more crucial factor for success. Making good decisions requires time, experience, and thorough problem-solving skills. In my research, through the analysis of scholarly sources, I have identified several role factors that clearly influence the decision-making process and its implementation. Furthermore, I have developed a self-designed questionnaire to examine the decision-making role in modern organizations. I analyzed the data from 230 respondents using various statistical methods. Based on my findings, conflict management, risk-taking, and a thorough understanding of the problem strongly determine leadership decision-making processes. The ability of leaders to effectively manage conflicts significantly impacts their decisions. Risk-taking is also of key importance, as leaders need to recognize the risks associated with a given situation and make decisions accordingly.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135696096","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.055
Ratesh Kumar, Jaya Gupta
A comparative study of scale-2 and scale-3 Haar wavelet has been presented to illustrate the level of accuracy attained by both the wavelets by applying on higher order differential equations known as Emden fowler equation, which has great importance in the field of astrophysics. Approximation of space variable is done by scale-2 and scale-3 Haar wavelet method by choosing different scales. The method is tested upon several test problems. The results are computed and compared in the form of absolute errors. The numerical tests confirm the accuracy, applicability and efficiency of the proposed method with different levels using both the wavelets. By the help of MATLAB algorithm simplification of the computational process is done.
{"title":"A Comparative Study using Scale-2 and Scale-3 Haar Wavelet for the Solution of Higher Order Differential Equation","authors":"Ratesh Kumar, Jaya Gupta","doi":"10.33889/ijmems.2023.8.5.055","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.055","url":null,"abstract":"A comparative study of scale-2 and scale-3 Haar wavelet has been presented to illustrate the level of accuracy attained by both the wavelets by applying on higher order differential equations known as Emden fowler equation, which has great importance in the field of astrophysics. Approximation of space variable is done by scale-2 and scale-3 Haar wavelet method by choosing different scales. The method is tested upon several test problems. The results are computed and compared in the form of absolute errors. The numerical tests confirm the accuracy, applicability and efficiency of the proposed method with different levels using both the wavelets. By the help of MATLAB algorithm simplification of the computational process is done.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43421297","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.051
N. Gupta, S. Prakash, Ashish Kumar
The goal of this study is to identify and evaluate key success factors (CSF) for unorganized retail supply chain management (UORSCM). The interpretative structural modelling (ISM) approach is applied for analyzing the CSFs. In India, the unorganized fast-moving consumer goods (FMCG) retail sector occupies a sizable amount of space and makes a significant GDP contribution. A total of 13 CSFs are analyzed, and to determine their driving and dependency power, MICMAC analysis is carried out. The outcome demonstrates that unorganized retailing suffers a variety of difficulties, like, the arrival of new competitors, product substitution, supplier problems, buyer threats, an increase in organized retailers, and co-manufacturer threats, in developing country settings. The factors with the highest positive impact are service quality in FMCG retail, time management at stores, product quality, and spoilage adjustment in retail. The factors, service quality in retail, time management at stores, and product quality have resulted in the highest driving power and lowest dependence power to attain the desired performance of UORSCM. The study’s findings also indicate that by focusing on these factors, unorganized retailers can efficiently handle customers.
{"title":"Ensuring the Success of Unorganized Retail Supply Chains of Current Times- A Developing Nation Perspective","authors":"N. Gupta, S. Prakash, Ashish Kumar","doi":"10.33889/ijmems.2023.8.5.051","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.051","url":null,"abstract":"The goal of this study is to identify and evaluate key success factors (CSF) for unorganized retail supply chain management (UORSCM). The interpretative structural modelling (ISM) approach is applied for analyzing the CSFs. In India, the unorganized fast-moving consumer goods (FMCG) retail sector occupies a sizable amount of space and makes a significant GDP contribution. A total of 13 CSFs are analyzed, and to determine their driving and dependency power, MICMAC analysis is carried out. The outcome demonstrates that unorganized retailing suffers a variety of difficulties, like, the arrival of new competitors, product substitution, supplier problems, buyer threats, an increase in organized retailers, and co-manufacturer threats, in developing country settings. The factors with the highest positive impact are service quality in FMCG retail, time management at stores, product quality, and spoilage adjustment in retail. The factors, service quality in retail, time management at stores, and product quality have resulted in the highest driving power and lowest dependence power to attain the desired performance of UORSCM. The study’s findings also indicate that by focusing on these factors, unorganized retailers can efficiently handle customers.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45729260","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.046
B. Aswin, Tapan Lokhande, R. Gaonkar
Reliability-based design is related to the performance analysis of engineering systems. The redundancy allocation problem is one of the most common problems in the reliability-based design approach. The redundancy allocation problem determines the redundancy level of components in a system to maximize system reliability, subject to several constraints. In recent years, obtaining solutions to reliability-related redundancy allocation problems by means of evolving meta-heuristic algorithms has appealed to researchers due to the several drawbacks of classical mathematical methods. Meta-heuristics have shown the potential of obtaining precise solution in optimization problems and many techniques have been applied in the literature for optimal redundancy allocation. In this paper, a recently developed Jaya optimization algorithm is proposed to be applied for redundancy allocation to maximize system reliability. The Jaya algorithm is a simple, population-based intelligent meta-heuristic algorithm consisting of a single phase and an algorithm-specific parameter-less algorithm. This paper aims to present an application of the Jaya algorithm for searching the optimal solution of two redundancy allocation problems from the literature with nonlinear constraints so that system reliability is maximized. The first problem is the over speed protection system for a gas turbine, whose control system is modelled as a four-stage series system. The objective is to determine the optimal level of redundancy of the valves of the protection system under cost and weight constraints. The second one is the redundancy allocation problem of a five-stage series system with volume, weight, and cost constraints. The results are validated by comparing them with two other meta-heuristics.
{"title":"Solving Redundancy Allocation Problems using Jaya Algorithm","authors":"B. Aswin, Tapan Lokhande, R. Gaonkar","doi":"10.33889/ijmems.2023.8.5.046","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.046","url":null,"abstract":"Reliability-based design is related to the performance analysis of engineering systems. The redundancy allocation problem is one of the most common problems in the reliability-based design approach. The redundancy allocation problem determines the redundancy level of components in a system to maximize system reliability, subject to several constraints. In recent years, obtaining solutions to reliability-related redundancy allocation problems by means of evolving meta-heuristic algorithms has appealed to researchers due to the several drawbacks of classical mathematical methods. Meta-heuristics have shown the potential of obtaining precise solution in optimization problems and many techniques have been applied in the literature for optimal redundancy allocation. In this paper, a recently developed Jaya optimization algorithm is proposed to be applied for redundancy allocation to maximize system reliability. The Jaya algorithm is a simple, population-based intelligent meta-heuristic algorithm consisting of a single phase and an algorithm-specific parameter-less algorithm. This paper aims to present an application of the Jaya algorithm for searching the optimal solution of two redundancy allocation problems from the literature with nonlinear constraints so that system reliability is maximized. The first problem is the over speed protection system for a gas turbine, whose control system is modelled as a four-stage series system. The objective is to determine the optimal level of redundancy of the valves of the protection system under cost and weight constraints. The second one is the redundancy allocation problem of a five-stage series system with volume, weight, and cost constraints. The results are validated by comparing them with two other meta-heuristics.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45968810","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.060
Joseph Nelson, Chungath Srinivasan, K. V. Lakshmy
Boolean functions form the fundamental components of symmetric cryptographic systems, serving as the building blocks. Modifying bent functions makes it feasible to design Boolean functions with desired properties that exhibit high non-linearity. The current study offers a comprehensive analysis of bent functions through its support, culminating in the introduction of an algorithm for the systematic construction of four variable bent functions. This algorithm enables the complete generation of all 896 four-variable bent functions. Furthermore, we introduce a methodology for constructing n-variable bent functions (where n > 4), leveraging both the algorithm and an established secondary technique for bent function construction. Lastly, we examine the estimation of the count of bent functions by utilising certain properties associated with the support of bent functions.
{"title":"An Algorithm for Constructing Support of Bent Functions by Extending a Set","authors":"Joseph Nelson, Chungath Srinivasan, K. V. Lakshmy","doi":"10.33889/ijmems.2023.8.5.060","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.060","url":null,"abstract":"Boolean functions form the fundamental components of symmetric cryptographic systems, serving as the building blocks. Modifying bent functions makes it feasible to design Boolean functions with desired properties that exhibit high non-linearity. The current study offers a comprehensive analysis of bent functions through its support, culminating in the introduction of an algorithm for the systematic construction of four variable bent functions. This algorithm enables the complete generation of all 896 four-variable bent functions. Furthermore, we introduce a methodology for constructing n-variable bent functions (where n > 4), leveraging both the algorithm and an established secondary technique for bent function construction. Lastly, we examine the estimation of the count of bent functions by utilising certain properties associated with the support of bent functions.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49283998","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.047
Sai Ganga, Z. Uddin, R. Asthana, H. Hassan, Arpit Bhardwaj
In this study, a variety of machine-learning algorithms are used to predict the viscosity and thermal conductivity of several water-based nanofluids. Machine learning algorithms, namely decision tree, random forest, extra tree, KNN, and polynomial regression, have been used, and their performances have been compared. The input parameters for the prediction of the thermal conductivity of nanofluids include temperature, concentration, and the thermal conductivity of nanoparticles. A three-input and a two-input model were utilized in modelling the viscosity of nanofluid. Both models considered temperature and concentration as input parameters, and additionally, the type of nanoparticle was considered for the three-input model. The order of importance of the most influential parameters in predicting both viscosity and thermal conductivity was studied. A wider range of input parameters have been considered in an open-access database. With the existing experimental data, all of the developed machine learning models exhibit reasonable agreement. Extra trees were found to provide the best results for estimating thermal conductivity, with a value of 0.9403. In predicting viscosity using a three-input model, extra trees were found to provide the best result with a value of 0.9771, and decision trees were found to provide the best results for estimating the viscosity using a two-input model with a value of 0.9678. In order to study heat transport phenomena through mathematical modelling, it is important to have an explicit mathematical expression. Therefore, the formulation of mathematical expressions for predicting viscosity and thermal conductivity has been carried out. Additionally, a comparison with the Xue and Maxwell thermal conductivity models is made to validate the results of this study, and the results are observed to be reliable.
{"title":"Modelling of Viscosity and Thermal Conductivity of Water-Based Nanofluids using Machine-Learning Techniques","authors":"Sai Ganga, Z. Uddin, R. Asthana, H. Hassan, Arpit Bhardwaj","doi":"10.33889/ijmems.2023.8.5.047","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.047","url":null,"abstract":"In this study, a variety of machine-learning algorithms are used to predict the viscosity and thermal conductivity of several water-based nanofluids. Machine learning algorithms, namely decision tree, random forest, extra tree, KNN, and polynomial regression, have been used, and their performances have been compared. The input parameters for the prediction of the thermal conductivity of nanofluids include temperature, concentration, and the thermal conductivity of nanoparticles. A three-input and a two-input model were utilized in modelling the viscosity of nanofluid. Both models considered temperature and concentration as input parameters, and additionally, the type of nanoparticle was considered for the three-input model. The order of importance of the most influential parameters in predicting both viscosity and thermal conductivity was studied. A wider range of input parameters have been considered in an open-access database. With the existing experimental data, all of the developed machine learning models exhibit reasonable agreement. Extra trees were found to provide the best results for estimating thermal conductivity, with a value of 0.9403. In predicting viscosity using a three-input model, extra trees were found to provide the best result with a value of 0.9771, and decision trees were found to provide the best results for estimating the viscosity using a two-input model with a value of 0.9678. In order to study heat transport phenomena through mathematical modelling, it is important to have an explicit mathematical expression. Therefore, the formulation of mathematical expressions for predicting viscosity and thermal conductivity has been carried out. Additionally, a comparison with the Xue and Maxwell thermal conductivity models is made to validate the results of this study, and the results are observed to be reliable.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45482496","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.059
Shagun Sharma, Kalpna Guleria, Sushil Kumar, S. Tiwari
Skin diseases are commonly identified problems all over the world. There are various kinds of skin diseases, such as skin cancer, vulgaris, ichthyosis, and eczema. Vitiligo is one of the skin diseases that can occur in any area of the body, including the inner part of the mouth. This type of skin can have immense negative impacts on the human body, involving memory issues, hypertension, and mental health problems. Conventionally, dermatologists use biopsy, blood tests, and patch testing to identify the presence of skin diseases and provide medications to patients. However, these treatments don't always provide results due to the transformation of a macule into a patch. Various machine learning (ML) and deep learning (DL) models have been developed for the early identification of macules to avoid delays in treatments. This work has implemented a DL-based model for predicting and classifying vitiligo skin disease in healthy skin. The features from the images have been extracted using a pre-trained Inception V3 model and substituted for each classifier, namely, naive Bayes, convolutional neural network (CNN), random forest, and decision tree. The results have been determined as accuracy, recall, precision, area under the curve (AUC), and F1-score for Inception V3 with naive Bayes as 99.5%, 0.995, 0.995, 0.997, and 0.995, respectively. The Inception V3 with CNN has achieved 99.8% accuracy, 0.998 recall, 0.998 precision, 1.00 AUC, and 0.998 F1-score. Further, Inception V3 with random forest shows 99.9% accuracy, 0.999 recall, 0.999 precision, 1.00 AUC, and 0.999 F1-score values whereas, Inception V3 with decision tree classifier shows an accuracy value of 97.8%, 0.978 recall, 0.977 precision, 0.969 AUC, and 0.977 F1-score. Results exhibit that Inception V3 with a random forest classifier outperforms in terms of accuracy, recall, precision, and F1-score, whereas for the AUC metric, Inception V3 with a random forest and Inception V3 with CNN have shown the same outcomes of 1.00.
{"title":"Deep Learning based Model for Detection of Vitiligo Skin Disease using Pre-trained Inception V3","authors":"Shagun Sharma, Kalpna Guleria, Sushil Kumar, S. Tiwari","doi":"10.33889/ijmems.2023.8.5.059","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.059","url":null,"abstract":"Skin diseases are commonly identified problems all over the world. There are various kinds of skin diseases, such as skin cancer, vulgaris, ichthyosis, and eczema. Vitiligo is one of the skin diseases that can occur in any area of the body, including the inner part of the mouth. This type of skin can have immense negative impacts on the human body, involving memory issues, hypertension, and mental health problems. Conventionally, dermatologists use biopsy, blood tests, and patch testing to identify the presence of skin diseases and provide medications to patients. However, these treatments don't always provide results due to the transformation of a macule into a patch. Various machine learning (ML) and deep learning (DL) models have been developed for the early identification of macules to avoid delays in treatments. This work has implemented a DL-based model for predicting and classifying vitiligo skin disease in healthy skin. The features from the images have been extracted using a pre-trained Inception V3 model and substituted for each classifier, namely, naive Bayes, convolutional neural network (CNN), random forest, and decision tree. The results have been determined as accuracy, recall, precision, area under the curve (AUC), and F1-score for Inception V3 with naive Bayes as 99.5%, 0.995, 0.995, 0.997, and 0.995, respectively. The Inception V3 with CNN has achieved 99.8% accuracy, 0.998 recall, 0.998 precision, 1.00 AUC, and 0.998 F1-score. Further, Inception V3 with random forest shows 99.9% accuracy, 0.999 recall, 0.999 precision, 1.00 AUC, and 0.999 F1-score values whereas, Inception V3 with decision tree classifier shows an accuracy value of 97.8%, 0.978 recall, 0.977 precision, 0.969 AUC, and 0.977 F1-score. Results exhibit that Inception V3 with a random forest classifier outperforms in terms of accuracy, recall, precision, and F1-score, whereas for the AUC metric, Inception V3 with a random forest and Inception V3 with CNN have shown the same outcomes of 1.00.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43065641","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.049
Sandeep Kumar, A. Singh, Ashutosh Mishra
This paper presents a compact microstrip-based dual-band antenna for terahertz (THz) technology, catering to the increasing demand for high-frequency, high-gain, and wideband THz antennas. THz technology has numerous applications, including its demands in bioinformatics and healthcare. To address this need, the proposed antenna operates in two frequency bands: 3.6 THz to 4.3 THz and 5 THz to 5.7 THz, enabling its use in THz band communication. The antenna design features a microstrip patch with two transverse slots and one longitudinal slot as a radiator, fed with a microstrip line. The transverse slots enable dual-band resonance, while the longitudinal slots enhance bandwidth and efficiency. Using a 10µm thick polyamide material with a dielectric constant of 3.55, the antenna achieves a compact size of 40 × 40 µm2, lightweight construction, high radiation efficiency, and a wide impedance bandwidth. Simulation results confirm good impedance matching characteristics, with minimal voltage standing wave ratio and return loss of -10dB or less. The antenna exhibits an impedance bandwidth of -10dB at 700 GHz, a peak radiation efficiency of 85%, a peak gain of 7.86 dB, and an omnidirectional radiation pattern. These favorable attributes position the proposed antenna as an excellent choice for various THz applications, particularly in bioinformatics and healthcare applications.
{"title":"Design and Analysis of Novel Microstrip-Based Dual-Band Compact Terahertz Antenna for Bioinformatics and Healthcare Applications","authors":"Sandeep Kumar, A. Singh, Ashutosh Mishra","doi":"10.33889/ijmems.2023.8.5.049","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.049","url":null,"abstract":"This paper presents a compact microstrip-based dual-band antenna for terahertz (THz) technology, catering to the increasing demand for high-frequency, high-gain, and wideband THz antennas. THz technology has numerous applications, including its demands in bioinformatics and healthcare. To address this need, the proposed antenna operates in two frequency bands: 3.6 THz to 4.3 THz and 5 THz to 5.7 THz, enabling its use in THz band communication. The antenna design features a microstrip patch with two transverse slots and one longitudinal slot as a radiator, fed with a microstrip line. The transverse slots enable dual-band resonance, while the longitudinal slots enhance bandwidth and efficiency. Using a 10µm thick polyamide material with a dielectric constant of 3.55, the antenna achieves a compact size of 40 × 40 µm2, lightweight construction, high radiation efficiency, and a wide impedance bandwidth. Simulation results confirm good impedance matching characteristics, with minimal voltage standing wave ratio and return loss of -10dB or less. The antenna exhibits an impedance bandwidth of -10dB at 700 GHz, a peak radiation efficiency of 85%, a peak gain of 7.86 dB, and an omnidirectional radiation pattern. These favorable attributes position the proposed antenna as an excellent choice for various THz applications, particularly in bioinformatics and healthcare applications.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46740042","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.057
Trust Tawanda, E. Munapo, Santosh Kumar, Philimon Nyamugure
Shortest path problem (SPP) has various applications in areas such as telecommunications, transportation and emergency services, and postal services among others. As a result, several algorithms have been developed to solve the SPP and related problems. The current paper extends the TANYAKUMU labelling method for solving the Travelling salesman problem (TSP) to solve SPP in directed transportation networks. Numerical illustrations are used to prove the validity of the proposed method. The main contributions of this paper are as follows: (i) modification of TSP algorithm to solve single source SPP, (ii) the developed method numerically evaluated on four increasingly complex problems of sizes 11×11, 21×21, 23×23 and 26×26 and lastly (iii) the solutions obtained from solving these four problems are compared with those obtained by Minimum incoming weight label (MIWL) algorithm. The proposed algorithm computed the same shortest paths as the MIWL algorithm on all four problems.
{"title":"Extended TANYAKUMU Labelling Method to Compute Shortest Paths in Directed Networks","authors":"Trust Tawanda, E. Munapo, Santosh Kumar, Philimon Nyamugure","doi":"10.33889/ijmems.2023.8.5.057","DOIUrl":"https://doi.org/10.33889/ijmems.2023.8.5.057","url":null,"abstract":"Shortest path problem (SPP) has various applications in areas such as telecommunications, transportation and emergency services, and postal services among others. As a result, several algorithms have been developed to solve the SPP and related problems. The current paper extends the TANYAKUMU labelling method for solving the Travelling salesman problem (TSP) to solve SPP in directed transportation networks. Numerical illustrations are used to prove the validity of the proposed method. The main contributions of this paper are as follows: (i) modification of TSP algorithm to solve single source SPP, (ii) the developed method numerically evaluated on four increasingly complex problems of sizes 11×11, 21×21, 23×23 and 26×26 and lastly (iii) the solutions obtained from solving these four problems are compared with those obtained by Minimum incoming weight label (MIWL) algorithm. The proposed algorithm computed the same shortest paths as the MIWL algorithm on all four problems.","PeriodicalId":44185,"journal":{"name":"International Journal of Mathematical Engineering and Management Sciences","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49639726","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 : 2023-10-01DOI: 10.33889/ijmems.2023.8.5.056
B. Joshi, Navneet Joshi, A. Gegov
Many criteria must be taken into account while selecting the best renewable energy source (RES), which necessitates a sophisticated multi-criteria decision-making (MCDM) procedure. Conflicting norms, as well as insufficient and inaccurate information, make this endeavour challenging. The theory of moderator intuitionistic fuzzy set (MIFS), a generalization of intuitionistic fuzzy sets (IFSs) has been developed to handle these uncertainties. The MIFS also helps to get a higher degree of precision in the uncertain behaviours due to the moderator parameter. In this paper, first some distance measures are presented for MIFSs, and then, on the basis of the proposed distances, we suggest a TOPSIS technique for choosing the best RES inside MIFS architecture. The efficacy of the proposed MIFS-based TOPSIS technique is put to the test by comparing different wind generating systems in a case study. The findings of the study are then compared in order to demonstrate that the suggested method is superior to the existing ones.
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