Pub Date : 2023-07-21DOI: 10.22581/muet1982.2303.06
ReddyPriya Madupuri, Dinesh Reddy Vemula, Anil Carie Chettupally, A. Sangi, Palla Ravi
The agriculture sector is one of the major sectors in India. India is well known for the production of various varieties of spices, fruits, vegetables, herbs, etc. Along with the pollution, the diseases that are affecting plants are increasing and there are various reasons for this. Tomato is one of the high-demand crops in the market and is produced in large quantities. There are many diseases that tomatoes get affected by because of the virus, fungus, bacteria, etc. In this project, we proposed a model to identify the diseases of tomato plants using images of tomato plant leaves. Our main goal is to develop a good model with decent accuracy and a mobile application that works with or without the internet for users, especially farmers. The Convolution Neural Network-based approach is used to create the model for this project. This proposed system model gives 98 % accuracy and that model is converted to the TF Lite model which is used in the application. This application can precisely predict the disease of the tomato leaf and suggest the treatment for it.
{"title":"Deep learning image-based automated application on classification of tomato leaf disease by pre-trained deep convolutional neural networks","authors":"ReddyPriya Madupuri, Dinesh Reddy Vemula, Anil Carie Chettupally, A. Sangi, Palla Ravi","doi":"10.22581/muet1982.2303.06","DOIUrl":"https://doi.org/10.22581/muet1982.2303.06","url":null,"abstract":"The agriculture sector is one of the major sectors in India. India is well known for the production of various varieties of spices, fruits, vegetables, herbs, etc. Along with the pollution, the diseases that are affecting plants are increasing and there are various reasons for this. Tomato is one of the high-demand crops in the market and is produced in large quantities. There are many diseases that tomatoes get affected by because of the virus, fungus, bacteria, etc. In this project, we proposed a model to identify the diseases of tomato plants using images of tomato plant leaves. Our main goal is to develop a good model with decent accuracy and a mobile application that works with or without the internet for users, especially farmers. The Convolution Neural Network-based approach is used to create the model for this project. This proposed system model gives 98 % accuracy and that model is converted to the TF Lite model which is used in the application. This application can precisely predict the disease of the tomato leaf and suggest the treatment for it.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46859765","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 : 2023-07-21DOI: 10.22581/muet1982.2303.02
Zeeshan Khatri, F. Ahmed, I. Kim
To fulfil the demand for eco-friendly nanomaterials, electrospinning offers a viable method for creating sustainable nanofibers. This mini review focuses on environmentally friendly and sustainability aspect of nanofibers produced via electrospinning. It examines difficulties and possibilities in ecologically friendly electrospinning, such as selecting environmentally friendly materials, reusing solvents, and using environmentally friendly additives. The use of biodegradable synthetic polymers, hybrid/composite nanofibers for improved performance, and natural polymers from renewable resources are only a few of the green electrospinning approaches that are covered. The review emphasises on green practices and sustainable challenges and opportunities. This review gives insight into green electrospinning techniques and the applications are also highlighted in tissue engineering, environmental remediation, energy storage, and environmentally friendly packaging. Further, the scalability, interdisciplinary cooperation, and regulatory issues are only a few of the obstacles and future directions that are discussed. A greener and more sustainable future in materials science is possible thanks to green electrospinning.
{"title":"Green electrospinning of sustainable nanofibers: a sustainable frontier for next-generation materials","authors":"Zeeshan Khatri, F. Ahmed, I. Kim","doi":"10.22581/muet1982.2303.02","DOIUrl":"https://doi.org/10.22581/muet1982.2303.02","url":null,"abstract":"To fulfil the demand for eco-friendly nanomaterials, electrospinning offers a viable method for creating sustainable nanofibers. This mini review focuses on environmentally friendly and sustainability aspect of nanofibers produced via electrospinning. It examines difficulties and possibilities in ecologically friendly electrospinning, such as selecting environmentally friendly materials, reusing solvents, and using environmentally friendly additives. The use of biodegradable synthetic polymers, hybrid/composite nanofibers for improved performance, and natural polymers from renewable resources are only a few of the green electrospinning approaches that are covered. The review emphasises on green practices and sustainable challenges and opportunities. This review gives insight into green electrospinning techniques and the applications are also highlighted in tissue engineering, environmental remediation, energy storage, and environmentally friendly packaging. Further, the scalability, interdisciplinary cooperation, and regulatory issues are only a few of the obstacles and future directions that are discussed. A greener and more sustainable future in materials science is possible thanks to green electrospinning.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42124190","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 : 2023-07-21DOI: 10.22581/muet1982.2303.05
Muhammad Adil Sultan, Salah Din, M. Ahsan, Shahan Cheema, M. Asim
Fine aggregate plays a key role as a filler material in concrete’s fresh and hardened properties. Generally, in Portland cement concrete aggregate occupies 70-85% by weight and 60-70% by mass. In Pakistan, Lawrence pur the sand as the only sand that meets the ASTM standards. But due to heavy transportation costs, it is not cost-effective to use in most parts of the country. The tests were carried out in accordance with ASTM standards, and the concrete mix designed with three water-cement ratios of 0.40,0.45, and 0.50 called for a mixing procedure. At 28 days of curing, an M30 concrete mix comprising five control mixes including parent concrete was evaluated and compared to parent concrete. This experimental work aimed to enhance the fresh and hardened properties of concrete such as the workability of concrete mix, compressive, and flexural strengths by using locally available Jhelum River sand gradation crushed sand (passing sieve #4, the waste product of Sargodha coarse aggregate), s a fine aggregate material. Using six sigma DMAIC Methodology 9 defects in the Jhelum River sand and control mix have been identified and corrective measures were taken to improve the quality of the concrete mix. The results derived from this experimental work show that adding 50% crushed sand in Jhelum River sand increases compressive strength by 27% and flexural strength by 20% which makes it according to ASTM Standards. The use of crushed sand as an alternative to natural river sand efficient and safe material. This control mix also reduces the construction cost by 10% in comparison to lawerancepur sand.
{"title":"The empirical study of gradation of crushed sand concrete properties using six sigma DMAIC methodology","authors":"Muhammad Adil Sultan, Salah Din, M. Ahsan, Shahan Cheema, M. Asim","doi":"10.22581/muet1982.2303.05","DOIUrl":"https://doi.org/10.22581/muet1982.2303.05","url":null,"abstract":"Fine aggregate plays a key role as a filler material in concrete’s fresh and hardened properties. Generally, in Portland cement concrete aggregate occupies 70-85% by weight and 60-70% by mass. In Pakistan, Lawrence pur the sand as the only sand that meets the ASTM standards. But due to heavy transportation costs, it is not cost-effective to use in most parts of the country. The tests were carried out in accordance with ASTM standards, and the concrete mix designed with three water-cement ratios of 0.40,0.45, and 0.50 called for a mixing procedure. At 28 days of curing, an M30 concrete mix comprising five control mixes including parent concrete was evaluated and compared to parent concrete. This experimental work aimed to enhance the fresh and hardened properties of concrete such as the workability of concrete mix, compressive, and flexural strengths by using locally available Jhelum River sand gradation crushed sand (passing sieve #4, the waste product of Sargodha coarse aggregate), s a fine aggregate material. Using six sigma DMAIC Methodology 9 defects in the Jhelum River sand and control mix have been identified and corrective measures were taken to improve the quality of the concrete mix. The results derived from this experimental work show that adding 50% crushed sand in Jhelum River sand increases compressive strength by 27% and flexural strength by 20% which makes it according to ASTM Standards. The use of crushed sand as an alternative to natural river sand efficient and safe material. This control mix also reduces the construction cost by 10% in comparison to lawerancepur sand.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43266411","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 : 2023-07-21DOI: 10.22581/muet1982.2303.07
A. Shaikh, N. Memon, Aneel Kumar, Ghulam Yasin Shaikh
Exponential deterioration in pavement caused by heavy loads, temperature variations, and heavy rainfall had led to pavement failure. To overcome those failures, bitumen properties needed to be enhanced in an economical and sustainable way. Researchers have used various modifiers to enhance the properties of virgin bitumen, but the end product still does not seem to be accepted by the asphalt industry at the required level. On the other hand, the construction cost has also increased due to the addition of modifiers, which have varying performance characteristics. To address such issues, waste materials such as crumb rubber obtained from waste tyres are used to enhance the properties of bitumen. The incorporation of crumb rubber has enhanced the properties of bitumen and has been well proven for decades. However, the product is still not widely accepted due to limitations such as consistency and uniformity during and after the production stages. In this research, crumb rubber was converted into pyrolyzed oil using a pyrolysis protocol and it was observed through the values of penetration and softening point test shows that optimum 2% pyrolyzed oil can be treated with bitumen to increase workability and flowability at low temperatures, such that additional crumb rubber in crumb form can be added homogenously. The results showed that an optimum quantity of 20% crumb rubber by mass of bitumen can be blended with pyrolyzed modified bitumen that is 5% crumb rubber more compared to untreated modified crumb rubber bitumen, which simultaneously increases the physical and mechanical properties of the mix. It enhances the softening point, viscosity, and storage stability while decreasing the penetration value.
{"title":"Performance characterization of crumb rubber modified bitumen using pyrolyzed waste tyre treated bitumen","authors":"A. Shaikh, N. Memon, Aneel Kumar, Ghulam Yasin Shaikh","doi":"10.22581/muet1982.2303.07","DOIUrl":"https://doi.org/10.22581/muet1982.2303.07","url":null,"abstract":"Exponential deterioration in pavement caused by heavy loads, temperature variations, and heavy rainfall had led to pavement failure. To overcome those failures, bitumen properties needed to be enhanced in an economical and sustainable way. Researchers have used various modifiers to enhance the properties of virgin bitumen, but the end product still does not seem to be accepted by the asphalt industry at the required level. On the other hand, the construction cost has also increased due to the addition of modifiers, which have varying performance characteristics. To address such issues, waste materials such as crumb rubber obtained from waste tyres are used to enhance the properties of bitumen. The incorporation of crumb rubber has enhanced the properties of bitumen and has been well proven for decades. However, the product is still not widely accepted due to limitations such as consistency and uniformity during and after the production stages. In this research, crumb rubber was converted into pyrolyzed oil using a pyrolysis protocol and it was observed through the values of penetration and softening point test shows that optimum 2% pyrolyzed oil can be treated with bitumen to increase workability and flowability at low temperatures, such that additional crumb rubber in crumb form can be added homogenously. The results showed that an optimum quantity of 20% crumb rubber by mass of bitumen can be blended with pyrolyzed modified bitumen that is 5% crumb rubber more compared to untreated modified crumb rubber bitumen, which simultaneously increases the physical and mechanical properties of the mix. It enhances the softening point, viscosity, and storage stability while decreasing the penetration value.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42304075","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 : 2023-07-21DOI: 10.22581/muet1982.2303.08
U. Khan, Tariq Rahim Soomro, Zheng Kougen
Fog computing offers an optimal answer to the expansion challenge of today’s networks. It boasts scaling and reduced latency. Since the concept is still nascent, many research questions remain unanswered. One of these is the challenge of Resource Management. There is a pressing need for a reliable and scalable architecture that meets the Resource Management challenge without compromising the Quality of Service. Among the proposed solutions, Artificial Intelligence based path selection techniques and automated link detection methods can provide lasting and reliable answer. An optimal approach for introducing intelligence in the networks is the infusion of Machine learning methods. Such futuristic, intelligent networks form the backbone of the next generation of Internet. These self-learning and self-healing networks are termed as the Zero-Touch networks. This paper proposes FedFog, a Federated Learning based optimal, automated Resource Management framework in Fog Computing for Zero-touch Networks. The paper describes a series of experiments focusing on Quality of Service parameters such as Network latency, Resources processed, Energy consumption and Network usage. The simulation results from these experiments depict superiority of the proposed architecture over traditional, existing architecture.
{"title":"FedFog - A federated learning based resource management framework in fog computing for zero touch networks","authors":"U. Khan, Tariq Rahim Soomro, Zheng Kougen","doi":"10.22581/muet1982.2303.08","DOIUrl":"https://doi.org/10.22581/muet1982.2303.08","url":null,"abstract":"Fog computing offers an optimal answer to the expansion challenge of today’s networks. It boasts scaling and reduced latency. Since the concept is still nascent, many research questions remain unanswered. One of these is the challenge of Resource Management. There is a pressing need for a reliable and scalable architecture that meets the Resource Management challenge without compromising the Quality of Service. Among the proposed solutions, Artificial Intelligence based path selection techniques and automated link detection methods can provide lasting and reliable answer. An optimal approach for introducing intelligence in the networks is the infusion of Machine learning methods. Such futuristic, intelligent networks form the backbone of the next generation of Internet. These self-learning and self-healing networks are termed as the Zero-Touch networks. This paper proposes FedFog, a Federated Learning based optimal, automated Resource Management framework in Fog Computing for Zero-touch Networks. The paper describes a series of experiments focusing on Quality of Service parameters such as Network latency, Resources processed, Energy consumption and Network usage. The simulation results from these experiments depict superiority of the proposed architecture over traditional, existing architecture.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49350131","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 : 2023-07-21DOI: 10.22581/muet1982.2303.14
Prem Kumar, Syed Feroz Shah, R. B. Khokhar, M. A. Uqaili, Laveet Kumar, Raja Fawad Zafar
A meteorological drought study is performed using monthly time scale data from three separate locations in southern Sindh, Pakistan. Rainfall and temperature have been used to identify the drought. These data were transformed into drought indices known as the standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI), which were derived using (the Hargreaves equation). In this study, two indices are compared for three separate meteorological stations Chhor, Mithi, and Badin where most socioeconomic livelihoods depend heavily on water. The SPEI is produced through a simple water balance combining precipitation and temperature, in distinction to the SPI, it just considers precipitation. In conclusion, our study showed that both indices were capable of detecting droughts that fluctuated in time across the reference period of 2004–2021. SPI and SPEI's direction of change was similar, however the impact on the drought condition varied. SPEI discovered more droughts with longer durations and greater with 13 moderate droughts at SPEI-3 for Chhor and Badin Station while Mithi indicated 8 moderate droughts during 2004-2021 and SPI-3 indicated 4 moderates for Chhor, Mithi and Badin indicated 6 moderate drought. Conversely, SPEI discovered more moderate-level droughts than SPI, however they were of shorter length and less frequent occurrence than the severe to moderate droughts. The findings imply that drought characteristics are significantly influenced by temperature variability.
{"title":"Meteorological drought mitigation for combating climate change: a case study of southern Sindh, Pakistan","authors":"Prem Kumar, Syed Feroz Shah, R. B. Khokhar, M. A. Uqaili, Laveet Kumar, Raja Fawad Zafar","doi":"10.22581/muet1982.2303.14","DOIUrl":"https://doi.org/10.22581/muet1982.2303.14","url":null,"abstract":"A meteorological drought study is performed using monthly time scale data from three separate locations in southern Sindh, Pakistan. Rainfall and temperature have been used to identify the drought. These data were transformed into drought indices known as the standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI), which were derived using (the Hargreaves equation). In this study, two indices are compared for three separate meteorological stations Chhor, Mithi, and Badin where most socioeconomic livelihoods depend heavily on water. The SPEI is produced through a simple water balance combining precipitation and temperature, in distinction to the SPI, it just considers precipitation. In conclusion, our study showed that both indices were capable of detecting droughts that fluctuated in time across the reference period of 2004–2021. SPI and SPEI's direction of change was similar, however the impact on the drought condition varied. SPEI discovered more droughts with longer durations and greater with 13 moderate droughts at SPEI-3 for Chhor and Badin Station while Mithi indicated 8 moderate droughts during 2004-2021 and SPI-3 indicated 4 moderates for Chhor, Mithi and Badin indicated 6 moderate drought. Conversely, SPEI discovered more moderate-level droughts than SPI, however they were of shorter length and less frequent occurrence than the severe to moderate droughts. The findings imply that drought characteristics are significantly influenced by temperature variability.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48467184","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 : 2023-07-21DOI: 10.22581/muet1982.2303.11
A. Pathan, T. Memon, Saleem Raza Memon, Rizwan Aziz Mangi
Digital Image Processing has dominated Digital Signal Processing at the cost of more memory, resources, and high computational power. In image processing, filtering transformations and other operations need complex multiplications, and the multiplier is one of the most resources consuming elements. Recently, mitigating the multiplier complexity in the digital signal processing (DSP) algorithms sigma-delta modulation based general purpose and adaptive DSP algorithms are developed in MATLAB and compared with its counterpart multi-bit algorithms for functionality and area-performance-power in FPGA. The contemporary multiplier algorithms are also optimized to overcome the multiplier complexity challenge as computation becomes simple and fast. This paper extends the reported work by investigating the sigma-delta modulation approaches for developing a computationally efficient low-power image processing algorithm. The proposed model is designed, developed, and simulated in MATLAB. The simulation results are analyzed using SNR, MSE, and Peak SNR. The simulation results show that the proposed system can better mitigate the noise effect, making it robust for noisy environment.
{"title":"Computationally efficient low-power sigma delta modulation-based image processing algorithm","authors":"A. Pathan, T. Memon, Saleem Raza Memon, Rizwan Aziz Mangi","doi":"10.22581/muet1982.2303.11","DOIUrl":"https://doi.org/10.22581/muet1982.2303.11","url":null,"abstract":"Digital Image Processing has dominated Digital Signal Processing at the cost of more memory, resources, and high computational power. In image processing, filtering transformations and other operations need complex multiplications, and the multiplier is one of the most resources consuming elements. Recently, mitigating the multiplier complexity in the digital signal processing (DSP) algorithms sigma-delta modulation based general purpose and adaptive DSP algorithms are developed in MATLAB and compared with its counterpart multi-bit algorithms for functionality and area-performance-power in FPGA. The contemporary multiplier algorithms are also optimized to overcome the multiplier complexity challenge as computation becomes simple and fast. This paper extends the reported work by investigating the sigma-delta modulation approaches for developing a computationally efficient low-power image processing algorithm. The proposed model is designed, developed, and simulated in MATLAB. The simulation results are analyzed using SNR, MSE, and Peak SNR. The simulation results show that the proposed system can better mitigate the noise effect, making it robust for noisy environment.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49666254","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 : 2023-07-21DOI: 10.22581/muet1982.2303.15
Khurram Shaikh, I. Hussain, B. S. Chowdhry
Maintenance of Railway rolling stock is usually scheduled based. However, the mechanical parts, especially the wheelset may wear down prematurely due to several factors such as excessive braking and traction forces and environmental conditions. This makes the scheduled maintenance less effective and sometimes it results in derailments. This paper presents a deep learning-based technique to detect wheel conditions so that maintenance can be performed promptly and efficiently. A time series dataset of axle vibrations is generated using a simulation model of the wheelset. The dataset is then used to train and test the deep learning model. Long short-term memory (LSTM) architecture is selected for this application since it is designed to perform better for time series datasets. The results show good performance in terms of training and testing accuracy. The model is tested in different defect scenarios and the mean square error in the prediction of railway wheelset parameters is around 15%.
{"title":"Deep learning-based fault detection in railway wheelsets using time series analysis","authors":"Khurram Shaikh, I. Hussain, B. S. Chowdhry","doi":"10.22581/muet1982.2303.15","DOIUrl":"https://doi.org/10.22581/muet1982.2303.15","url":null,"abstract":"Maintenance of Railway rolling stock is usually scheduled based. However, the mechanical parts, especially the wheelset may wear down prematurely due to several factors such as excessive braking and traction forces and environmental conditions. This makes the scheduled maintenance less effective and sometimes it results in derailments. This paper presents a deep learning-based technique to detect wheel conditions so that maintenance can be performed promptly and efficiently. A time series dataset of axle vibrations is generated using a simulation model of the wheelset. The dataset is then used to train and test the deep learning model. Long short-term memory (LSTM) architecture is selected for this application since it is designed to perform better for time series datasets. The results show good performance in terms of training and testing accuracy. The model is tested in different defect scenarios and the mean square error in the prediction of railway wheelset parameters is around 15%.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46205933","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 : 2023-07-21DOI: 10.22581/muet1982.2303.04
H. Jamshaid, Abdul Waqar Rajput, I. Bajwa, A. Mujeeb
Nowadays, denim is in trend. To achieve visually appealing results, various washing processes are applied to denim. For washing denim, a variety of methods are available, and they all produce distinct kinds of waste. These methods have various environmental effects. This study aims to examine the environmental impact of various denim washing effluents. Here, six different washes desizing, enzyme, stone, bleach, acid, and random wash are performed. In order to compare how washing affects both the environment and the fabric, effluent tests are carried out. Since enzymes are unique by nature, enzyme wash demonstrated the greatest GSM. They don't affect the fibre composition; they just break down the color that is on the surface of the cellulose. Shrinkage is the cause of the general rise in GSM. However, the thickness, pilling, and elongation % of the cloth were unaffected by the washing. Due to the alkaline nature of the washing procedure, which results in minimal harm to the cloth, the enzyme and desize wash exhibit high strength. The fabric's rigidity decreases when stone, bleach, and acid wash damage it, which raises the angle at which the crease recovers. Due to the use of enzyme and desize wash produces effluent with a reduced TDS. In these procedures, the indigo hue on the denim surface is diminished, which causes the fading to occur. This process results in less polluted water that is simpler for wastewater treatment plants to process.
{"title":"Effect of different washing methods on denim fabric properties and their effluent’s environmental impact","authors":"H. Jamshaid, Abdul Waqar Rajput, I. Bajwa, A. Mujeeb","doi":"10.22581/muet1982.2303.04","DOIUrl":"https://doi.org/10.22581/muet1982.2303.04","url":null,"abstract":"Nowadays, denim is in trend. To achieve visually appealing results, various washing processes are applied to denim. For washing denim, a variety of methods are available, and they all produce distinct kinds of waste. These methods have various environmental effects. This study aims to examine the environmental impact of various denim washing effluents. Here, six different washes desizing, enzyme, stone, bleach, acid, and random wash are performed. In order to compare how washing affects both the environment and the fabric, effluent tests are carried out. Since enzymes are unique by nature, enzyme wash demonstrated the greatest GSM. They don't affect the fibre composition; they just break down the color that is on the surface of the cellulose. Shrinkage is the cause of the general rise in GSM. However, the thickness, pilling, and elongation % of the cloth were unaffected by the washing. Due to the alkaline nature of the washing procedure, which results in minimal harm to the cloth, the enzyme and desize wash exhibit high strength. The fabric's rigidity decreases when stone, bleach, and acid wash damage it, which raises the angle at which the crease recovers. Due to the use of enzyme and desize wash produces effluent with a reduced TDS. In these procedures, the indigo hue on the denim surface is diminished, which causes the fading to occur. This process results in less polluted water that is simpler for wastewater treatment plants to process.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47041432","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 : 2023-07-21DOI: 10.22581/muet1982.2303.16
Muhammad Israr, M. Zia, N. Rehman, Imran Ullah, Khushal Khan
Globally, A leading cause of death is heart disease and a serious public health concern. The anomalies in heart sound appears before the heart disease symptoms. The sounds are type of auscultation, which is a process dealing with sounds in a body that generates due to mechanical vibrations of organs, Auscultation is a potential method in medical science to detect abnormalities in heart sounds and in case of suspicion The patient follows up with a referral for other evaluations, such as an electrocardiogram. In medical sciences early detection of symptoms are of major importance, this research work is a good step toward the detection of abnormalities in heart before symptom appearing by processing the phonocardiogram (PCG) signal. In this paper PCG signals are classified by utilizing the features of Mel frequency cepstral coefficients (MFCC) through Cartesian Genetic Programming - Artificial Network (CGP-ANN) Classifier. The diagnostic accuracy of proposed methodology is found 99.50% which is more than other classifiers like Support Vector Machine (SVM) and Convolutional Neural Network (CNN). The accuracy of model as compared to other models can prove the performance superiority of the proposed system.
{"title":"Classification of normal and abnormal heart by classifying PCG signal using MFCC coefficients and CGP-ANN classifier","authors":"Muhammad Israr, M. Zia, N. Rehman, Imran Ullah, Khushal Khan","doi":"10.22581/muet1982.2303.16","DOIUrl":"https://doi.org/10.22581/muet1982.2303.16","url":null,"abstract":"Globally, A leading cause of death is heart disease and a serious public health concern. The anomalies in heart sound appears before the heart disease symptoms. The sounds are type of auscultation, which is a process dealing with sounds in a body that generates due to mechanical vibrations of organs, Auscultation is a potential method in medical science to detect abnormalities in heart sounds and in case of suspicion The patient follows up with a referral for other evaluations, such as an electrocardiogram. In medical sciences early detection of symptoms are of major importance, this research work is a good step toward the detection of abnormalities in heart before symptom appearing by processing the phonocardiogram (PCG) signal. In this paper PCG signals are classified by utilizing the features of Mel frequency cepstral coefficients (MFCC) through Cartesian Genetic Programming - Artificial Network (CGP-ANN) Classifier. The diagnostic accuracy of proposed methodology is found 99.50% which is more than other classifiers like Support Vector Machine (SVM) and Convolutional Neural Network (CNN). The accuracy of model as compared to other models can prove the performance superiority of the proposed system.","PeriodicalId":44836,"journal":{"name":"Mehran University Research Journal of Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47219817","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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