Pub Date : 2023-04-03DOI: 10.22581/muet1982.2302.18
K. Mahboob, R. Asif, N. G. Haider
The career opportunities in computer programming are vast and rapidly increasing. Skilled software engineers, programmers, and developers are vigorously in demand worldwide. The capability to forecast a student's future career can be helpful in a wide variety of pedagogical practices. Data mining is becoming a more robust tool for analysis and forecasting. Therefore, to forecast career placement probabilities in the programming field, data mining classification and forecast techniques are used in this study to facilitate prospective students to make sensible career decisions. To achieve this objective, passed-out graduates' data is utilized, which comprises features like graduates' educational attainments in pre-university grades, i.e. grades of matriculation and intermediate, programming courses taught in early semesters along with the Cumulative Grade Point Average (CGPA) with the internship experience, gender, and family demographic information. Various multi-way Classification Trees are generated, which could help students to choose a branch with high career placement probabilities. From historical data, the Classification Trees have determined whether the branch is 'Good', 'Satisfactory', or 'Poor' based on the given information. The experimental findings indicate that all the features significantly influence the career placement probabilities in the programming field.
{"title":"A data mining approach to forecast students’ career placement probabilities and recommendations in the programming field","authors":"K. Mahboob, R. Asif, N. G. Haider","doi":"10.22581/muet1982.2302.18","DOIUrl":"https://doi.org/10.22581/muet1982.2302.18","url":null,"abstract":"The career opportunities in computer programming are vast and rapidly increasing. Skilled software engineers, programmers, and developers are vigorously in demand worldwide. The capability to forecast a student's future career can be helpful in a wide variety of pedagogical practices. Data mining is becoming a more robust tool for analysis and forecasting. Therefore, to forecast career placement probabilities in the programming field, data mining classification and forecast techniques are used in this study to facilitate prospective students to make sensible career decisions. To achieve this objective, passed-out graduates' data is utilized, which comprises features like graduates' educational attainments in pre-university grades, i.e. grades of matriculation and intermediate, programming courses taught in early semesters along with the Cumulative Grade Point Average (CGPA) with the internship experience, gender, and family demographic information. Various multi-way Classification Trees are generated, which could help students to choose a branch with high career placement probabilities. From historical data, the Classification Trees have determined whether the branch is 'Good', 'Satisfactory', or 'Poor' based on the given information. The experimental findings indicate that all the features significantly influence the career placement probabilities in the programming field.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47211900","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 : 2023-04-03DOI: 10.22581/muet1982.2302.12
A. Memon, Abdul Qadir Memon, M. A. Soomro, Muneeb Ayub Memon, Jam Shahzaib Khan Sahito
Cost overruns are a global challenge to successfully completing construction projects. Cost overrun has a substantial impact resulting in most construction projects failing to be completed. Several factors have contributed significantly to the industry's decline. The factors were discovered in the literature, assessed, and applied to the construction industry in Pakistan. This study scrutinized and identified the relationships between the factors causing cost overruns in the Pakistani construction industry using the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach. The structural model was created and tested with Smart-PLS software using data from a questionnaire survey of 131 construction practitioners. Six constructs were used to categorise the factors. The model identifies 21 critical factors in Pakistani construction projects, with resource management ranking first. Contract management issues can also contribute significantly to project cost overruns. Model assessment results indicate that the developed model has a substantial power of explaining the factors of cost performance while R2 value showed that 45.7% variance is explained by the model. The model developed model will serve as a jumping-off point for academics, researchers, and practitioners in developing a cost-control system. It is suggested that establishing an efficient and effective contract management protocol among stakeholders throughout the design and supervision stages is extremely beneficial for improving project cost performance and significantly reducing time overruns.
{"title":"Structural model of cost overrun factors affecting Pakistani construction projects","authors":"A. Memon, Abdul Qadir Memon, M. A. Soomro, Muneeb Ayub Memon, Jam Shahzaib Khan Sahito","doi":"10.22581/muet1982.2302.12","DOIUrl":"https://doi.org/10.22581/muet1982.2302.12","url":null,"abstract":"Cost overruns are a global challenge to successfully completing construction projects. Cost overrun has a substantial impact resulting in most construction projects failing to be completed. Several factors have contributed significantly to the industry's decline. The factors were discovered in the literature, assessed, and applied to the construction industry in Pakistan. This study scrutinized and identified the relationships between the factors causing cost overruns in the Pakistani construction industry using the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach. The structural model was created and tested with Smart-PLS software using data from a questionnaire survey of 131 construction practitioners. Six constructs were used to categorise the factors. The model identifies 21 critical factors in Pakistani construction projects, with resource management ranking first. Contract management issues can also contribute significantly to project cost overruns. Model assessment results indicate that the developed model has a substantial power of explaining the factors of cost performance while R2 value showed that 45.7% variance is explained by the model. The model developed model will serve as a jumping-off point for academics, researchers, and practitioners in developing a cost-control system. It is suggested that establishing an efficient and effective contract management protocol among stakeholders throughout the design and supervision stages is extremely beneficial for improving project cost performance and significantly reducing time overruns.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44643755","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 : 2023-04-03DOI: 10.22581/muet1982.2302.10
W. Sahito, Rabeea W Bazuhair
Any construction must be designed and built after the subsurface soil has been determined. The subsurface qualities of the soil are rendered by expensive, time-consuming, and risky operations, which on the other hand, raise the project's capital expenditure while also getting the engineering properties of distinct soil materials. Standard sampling techniques for boreholes are used for the assessment of the engineering properties of soil. But it is pretty costly, intrusive, and takes too much time. Therefore, a different method of determining the subsurface soil parameters is required. An alternate strategy for borehole sampling is to use geo-electrical techniques, such as electrical resistivity (ER). This research aims to ascertain the relationship between the electrical resistivity of various soils and their engineering characteristics. Without using the borehole sample method, appropriate correlations will aid in determining the subsurface soil parameters. Good correlations are obtained for the relationship of electrical resistivity against friction angle, cohesion and moisture content with an R2 value of 0.79, 0.41 and 0.66, respectively. The correlation of resistivity with unit weight showed a weak relationship due to typical soil behavior.
{"title":"Behavior of electrical resistivity against different soil properties","authors":"W. Sahito, Rabeea W Bazuhair","doi":"10.22581/muet1982.2302.10","DOIUrl":"https://doi.org/10.22581/muet1982.2302.10","url":null,"abstract":"Any construction must be designed and built after the subsurface soil has been determined. The subsurface qualities of the soil are rendered by expensive, time-consuming, and risky operations, which on the other hand, raise the project's capital expenditure while also getting the engineering properties of distinct soil materials. Standard sampling techniques for boreholes are used for the assessment of the engineering properties of soil. But it is pretty costly, intrusive, and takes too much time. Therefore, a different method of determining the subsurface soil parameters is required. An alternate strategy for borehole sampling is to use geo-electrical techniques, such as electrical resistivity (ER). This research aims to ascertain the relationship between the electrical resistivity of various soils and their engineering characteristics. Without using the borehole sample method, appropriate correlations will aid in determining the subsurface soil parameters. Good correlations are obtained for the relationship of electrical resistivity against friction angle, cohesion and moisture content with an R2 value of 0.79, 0.41 and 0.66, respectively. The correlation of resistivity with unit weight showed a weak relationship due to typical soil behavior.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43000900","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 : 2023-04-03DOI: 10.22581/muet1982.2302.17
Muhammad Imran Ghoto, Mazhar Hussain Balouch, Touqeer Ahmed Jummani, A. A. Memon
Solar-energy is a clean source of energy and photovoltaic (PV) panels are constructed from solar cells (SC) which convert energy of light into electricity without any environmental effect. The researchers and policy makers focus on the huge scale adoption of solar panels due to its cleaner production. However, there is non-linear behavior in current-voltage characteristics of solar panels and shortage of data in manufacturer’s datasheet. In order to enhance the efficiency of solar panels it is mandatory to develop the PV panels scheme accurately by extracting the basic parameters. In this research study a mathematical model of two different solar cell models is used such as Single Diode Model (SDM) and Double Diode Model (DDM). The Particle Swarm Optimization (PSO) is used to extract the five and seven unknown parameters of SDM and DDM. The algorithm runs with one thousand iterations to minimize the Root Mean Square Error (RMSE) where the RMSE is the vector of five unknown parameters for SDM and seven for DDM. The superiority of proposed PSO algorithm is proved by the optimized results of unrevealed parameters with minimized RMSE of up to 10-3. Optimum parameter values for the solar cell models are applied on the real time data of a 55 mm diameter commercial RTC-France SC. Finally, the results reveal that P-V and I-V curves exhibit smallest deviation between estimated and real time values. The results reveal that the proposed PSO converges to optimal solution with least number of iterations compared to the existing metaheuristic algorithms.
{"title":"Parameters extraction of photovoltaic cells using swarm intelligence based optimization technique: research on single diode model and double diode model","authors":"Muhammad Imran Ghoto, Mazhar Hussain Balouch, Touqeer Ahmed Jummani, A. A. Memon","doi":"10.22581/muet1982.2302.17","DOIUrl":"https://doi.org/10.22581/muet1982.2302.17","url":null,"abstract":"Solar-energy is a clean source of energy and photovoltaic (PV) panels are constructed from solar cells (SC) which convert energy of light into electricity without any environmental effect. The researchers and policy makers focus on the huge scale adoption of solar panels due to its cleaner production. However, there is non-linear behavior in current-voltage characteristics of solar panels and shortage of data in manufacturer’s datasheet. In order to enhance the efficiency of solar panels it is mandatory to develop the PV panels scheme accurately by extracting the basic parameters. In this research study a mathematical model of two different solar cell models is used such as Single Diode Model (SDM) and Double Diode Model (DDM). The Particle Swarm Optimization (PSO) is used to extract the five and seven unknown parameters of SDM and DDM. The algorithm runs with one thousand iterations to minimize the Root Mean Square Error (RMSE) where the RMSE is the vector of five unknown parameters for SDM and seven for DDM. The superiority of proposed PSO algorithm is proved by the optimized results of unrevealed parameters with minimized RMSE of up to 10-3. Optimum parameter values for the solar cell models are applied on the real time data of a 55 mm diameter commercial RTC-France SC. Finally, the results reveal that P-V and I-V curves exhibit smallest deviation between estimated and real time values. The results reveal that the proposed PSO converges to optimal solution with least number of iterations compared to the existing metaheuristic algorithms.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49023003","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 : 2023-04-03DOI: 10.22581/muet1982.2302.13
Muhammad Mateen Afzal Awan, Atif Ullah Khan, Mohammad Umer Siddiqui, Hamid Karim, Muhammad Bux
Conventional energy generation technologies face unreliability due to the depletion of fossil fuels, soaring energy prices, greenhouse gas emissions, and continuously increasing energy demand. As a result, researchers are searching for reliable, cheap, and environmentally friendly renewable energy technologies. Solar photovoltaic (PV) technology, which directly converts sunlight into electricity, is the most attractive sustainable energy source due to the sun's ubiquitous presence. However, the non-linear behaviour of solar PV demands maximum power point tracking (MPPT) to ensure optimal power production. Although Hill Climbing (HC) is a simple, cheap, and efficient MPPT algorithm, it has a drawback of steady-state oscillations around MPP under uniform weather conditions. To overcome this weakness, we propose some modifications in the tracking structure of the HC algorithm. The proposed optimized HC (OHC) algorithm achieves zero steady-state oscillations without compromising the strength of the conventional HC algorithm. We applied both algorithms to an off-grid PV system under constant and changing weather conditions, and the results demonstrate the superiority of the proposed OHC algorithm over the conventional HC algorithm.
{"title":"Optimized hill climbing algorithm for an islanded solar photovoltaic system","authors":"Muhammad Mateen Afzal Awan, Atif Ullah Khan, Mohammad Umer Siddiqui, Hamid Karim, Muhammad Bux","doi":"10.22581/muet1982.2302.13","DOIUrl":"https://doi.org/10.22581/muet1982.2302.13","url":null,"abstract":"Conventional energy generation technologies face unreliability due to the depletion of fossil fuels, soaring energy prices, greenhouse gas emissions, and continuously increasing energy demand. As a result, researchers are searching for reliable, cheap, and environmentally friendly renewable energy technologies. Solar photovoltaic (PV) technology, which directly converts sunlight into electricity, is the most attractive sustainable energy source due to the sun's ubiquitous presence. However, the non-linear behaviour of solar PV demands maximum power point tracking (MPPT) to ensure optimal power production. Although Hill Climbing (HC) is a simple, cheap, and efficient MPPT algorithm, it has a drawback of steady-state oscillations around MPP under uniform weather conditions. To overcome this weakness, we propose some modifications in the tracking structure of the HC algorithm. The proposed optimized HC (OHC) algorithm achieves zero steady-state oscillations without compromising the strength of the conventional HC algorithm. We applied both algorithms to an off-grid PV system under constant and changing weather conditions, and the results demonstrate the superiority of the proposed OHC algorithm over the conventional HC algorithm.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48548372","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 : 2023-04-03DOI: 10.22581/muet1982.2302.11
M. Memon, K. B. Amur, W. A. Shaikh
The goal of the work is to solve the nonlinear convection-diffusion-reaction problem using the variational iteration method with the combination of the Chebyshev wavelet. This work developed a hybrid iterative technique named as Variational iteration method with the Chebyshev wavelet for the solutions of nonlinear convection-diffusion-reaction problems. The aim of applying the derived algorithm is to achieve fast convergence. During the solution of the given problem, the restricted variations will be mathematically justified. The effects of the scaling and other parameters like diffusion parameter, convection parameter, and reaction parameter on the solution are also focused on by their suitable selection. The approximate results include the error profiles and the simulations. The results of variational iteration with the Chebyshev wavelet are compared with variational iteration method, the Modified variational iteration method, and the Variational iteration method with Legendre wavelet. The error profiles allow us to compare the results with well-known existing schemes.
{"title":"Combined variational iteration method with chebyshev wavelet for the solution of convection-diffusion-reaction problem","authors":"M. Memon, K. B. Amur, W. A. Shaikh","doi":"10.22581/muet1982.2302.11","DOIUrl":"https://doi.org/10.22581/muet1982.2302.11","url":null,"abstract":"The goal of the work is to solve the nonlinear convection-diffusion-reaction problem using the variational iteration method with the combination of the Chebyshev wavelet. This work developed a hybrid iterative technique named as Variational iteration method with the Chebyshev wavelet for the solutions of nonlinear convection-diffusion-reaction problems. The aim of applying the derived algorithm is to achieve fast convergence. During the solution of the given problem, the restricted variations will be mathematically justified. The effects of the scaling and other parameters like diffusion parameter, convection parameter, and reaction parameter on the solution are also focused on by their suitable selection. The approximate results include the error profiles and the simulations. The results of variational iteration with the Chebyshev wavelet are compared with variational iteration method, the Modified variational iteration method, and the Variational iteration method with Legendre wavelet. The error profiles allow us to compare the results with well-known existing schemes.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":"26 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68227035","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 : 2023-04-03DOI: 10.22581/muet1982.2302.09
Muhammad Akhtar, Saif-Ur Rehman
Product evaluations, ratings, and other sorts of online expressions have risen in popularity as a result of the emergence of social networking sites and blogs. Sentiment analysis has emerged as a new area of study for computational linguists as a result of this rapidly expanding data set. From around a decade ago, this has been a topic of discussion for English speakers. However, the scientific community completely ignores other important languages, such as Urdu. Morphologically, Urdu is one of the most complex languages in the world. For this reason, a variety of unique characteristics, such as the language's unusual morphology and unrestricted word order, make the Urdu language processing a difficult challenge to solve. This research provides a new framework for the categorization of Urdu language sentiments. The main contributions of the research are to show how important this multidimensional research problem is as well as its technical parts, such as the parsing algorithm, corpus, lexicon, etc. A new approach for Urdu text sentiment analysis including data gathering, pre-processing, feature extraction, feature vector formation, and finally, sentiment classification has been designed to deal with Urdu language sentiments. The result and discussion section provides a comprehensive comparison of the proposed work with the standard baseline method in terms of precision, recall, f-measure, and accuracy of three different types of datasets. In the overall comparison of the models, the proposed work shows an encouraging achievement in terms of accuracy and other metrics. Last but not least, this section also provides the featured trend and possible direction of the current work.
{"title":"A machine learning approach for Urdu text sentiment analysis","authors":"Muhammad Akhtar, Saif-Ur Rehman","doi":"10.22581/muet1982.2302.09","DOIUrl":"https://doi.org/10.22581/muet1982.2302.09","url":null,"abstract":"Product evaluations, ratings, and other sorts of online expressions have risen in popularity as a result of the emergence of social networking sites and blogs. Sentiment analysis has emerged as a new area of study for computational linguists as a result of this rapidly expanding data set. From around a decade ago, this has been a topic of discussion for English speakers. However, the scientific community completely ignores other important languages, such as Urdu. Morphologically, Urdu is one of the most complex languages in the world. For this reason, a variety of unique characteristics, such as the language's unusual morphology and unrestricted word order, make the Urdu language processing a difficult challenge to solve. This research provides a new framework for the categorization of Urdu language sentiments. The main contributions of the research are to show how important this multidimensional research problem is as well as its technical parts, such as the parsing algorithm, corpus, lexicon, etc. A new approach for Urdu text sentiment analysis including data gathering, pre-processing, feature extraction, feature vector formation, and finally, sentiment classification has been designed to deal with Urdu language sentiments. The result and discussion section provides a comprehensive comparison of the proposed work with the standard baseline method in terms of precision, recall, f-measure, and accuracy of three different types of datasets. In the overall comparison of the models, the proposed work shows an encouraging achievement in terms of accuracy and other metrics. Last but not least, this section also provides the featured trend and possible direction of the current work.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43464612","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 : 2023-04-03DOI: 10.22581/muet1982.2302.15
A. A. Memon, A. A. Memon, M. A. Uqaili, Mukhtiar Ali Unar
Switched Reluctance Machine (SRM) is the advanced version of the stepper motor and since last decade, it is of high interest among researchers and industrial applications. Modelling an SRM relies on accurate data and proper selection of parameters. The next step is the performance analysis of the machine for which losses determination is indispensable. Previous studies have shown losses calculation only at a particular instant of switching of the machine (i.e., conduction angle). Therefore, the impact of losses in a motoring region cannot be justified. This paper investigates the impact of varying conduction angle on the performance of machines for a set of switch-on angle. Losses are calculated and predicted through simulating motor operating parameters carried out in MATLAB environment and accuracy of results are compared with experimental results.
{"title":"Effect of variable conduction angle on the losses of switched reluctance machine","authors":"A. A. Memon, A. A. Memon, M. A. Uqaili, Mukhtiar Ali Unar","doi":"10.22581/muet1982.2302.15","DOIUrl":"https://doi.org/10.22581/muet1982.2302.15","url":null,"abstract":"Switched Reluctance Machine (SRM) is the advanced version of the stepper motor and since last decade, it is of high interest among researchers and industrial applications. Modelling an SRM relies on accurate data and proper selection of parameters. The next step is the performance analysis of the machine for which losses determination is indispensable. Previous studies have shown losses calculation only at a particular instant of switching of the machine (i.e., conduction angle). Therefore, the impact of losses in a motoring region cannot be justified. This paper investigates the impact of varying conduction angle on the performance of machines for a set of switch-on angle. Losses are calculated and predicted through simulating motor operating parameters carried out in MATLAB environment and accuracy of results are compared with experimental results.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44158775","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 : 2023-04-02DOI: 10.22581/muet1982.2302.07
Munib Ahmed, M. I. Baig
Due to advancements in multi-core design technology, IC (Integrated Circuits) designers have expanded the single chip multi-core design. A privileged way of communication effectively between these multi-cores is a Network on-chip (NoC). Design of an effective routing algorithm capable of routing data to non-congested paths is the most notable research challenge in NoC, by retrieving congestion information of non-local nodes. This research proposed an improved congestion-aware load balancing routing algorithm. Non-local or distant links congestion awareness is done by propagating congestion information via data packets. By counting number of hops from the source node, in the quadrant of the destination node, an intermediate node has been defined, and after the calculation of the least congested route to the intermediate node, this route is also stored in the data packet for source routing. Furthermore, for load balancing network is partitioned into two areas called high congested area (HCA) and low congested area (LCA). For load balancing, from HCA a node in LCA is selected as output for data packets. Comparison of the proposed algorithm is done in the form of average latency, average throughput, power consumption, and scalability analysis under synthetic traffic patterns. Under simulation experiments, it is shown improvement in an average latency and throughput of the proposed algorithm is 31.28% and 5.28% respectively, than existing.
{"title":"An improved non-local awareness of congestion and load balanced algorithm for the communication of on chip 2D mesh-based network","authors":"Munib Ahmed, M. I. Baig","doi":"10.22581/muet1982.2302.07","DOIUrl":"https://doi.org/10.22581/muet1982.2302.07","url":null,"abstract":"Due to advancements in multi-core design technology, IC (Integrated Circuits) designers have expanded the single chip multi-core design. A privileged way of communication effectively between these multi-cores is a Network on-chip (NoC). Design of an effective routing algorithm capable of routing data to non-congested paths is the most notable research challenge in NoC, by retrieving congestion information of non-local nodes. This research proposed an improved congestion-aware load balancing routing algorithm. Non-local or distant links congestion awareness is done by propagating congestion information via data packets. By counting number of hops from the source node, in the quadrant of the destination node, an intermediate node has been defined, and after the calculation of the least congested route to the intermediate node, this route is also stored in the data packet for source routing. Furthermore, for load balancing network is partitioned into two areas called high congested area (HCA) and low congested area (LCA). For load balancing, from HCA a node in LCA is selected as output for data packets. Comparison of the proposed algorithm is done in the form of average latency, average throughput, power consumption, and scalability analysis under synthetic traffic patterns. Under simulation experiments, it is shown improvement in an average latency and throughput of the proposed algorithm is 31.28% and 5.28% respectively, than existing.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42026049","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 : 2023-04-02DOI: 10.22581/muet1982.2302.08
Muhammad Mateen Afzal Awan, M. Awan, Atif Ullah Khan, Mohammad Umer, M. Zia, Muhammad Bux
In order to simplify the analysis of complex electronic systems, they needsto be modeled accurately. Model reduction is further required to streamline the procedural and computational complexities. Further the instability caused by the model reduction techniques worstly effects the accuracy of a system. Therefore, we have proposed some improvements in the frequency limited impulse response Gramians based model order reduction techniques for discrete time systems. The propsed techniques assures the stability of the model after it get reduced. The proposed techniques provided better results than the stability preserving techniques.
{"title":"Frequency limited impulse response gramians based model reduction","authors":"Muhammad Mateen Afzal Awan, M. Awan, Atif Ullah Khan, Mohammad Umer, M. Zia, Muhammad Bux","doi":"10.22581/muet1982.2302.08","DOIUrl":"https://doi.org/10.22581/muet1982.2302.08","url":null,"abstract":"In order to simplify the analysis of complex electronic systems, they needsto be modeled accurately. Model reduction is further required to streamline the procedural and computational complexities. Further the instability caused by the model reduction techniques worstly effects the accuracy of a system. Therefore, we have proposed some improvements in the frequency limited impulse response Gramians based model order reduction techniques for discrete time systems. The propsed techniques assures the stability of the model after it get reduced. The proposed techniques provided better results than the stability preserving techniques.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48849816","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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