Pub Date : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9074107
Dodo Khan, L. T. Jung, Manzoor Ahmed Hashmani, A. Waqas
The state-of-art Blockchain technology has been receiving enormous attention from researchers and industry practitioners in recent years. Basically Blockchain is a distributed immutable ledgerutilized by user mainly to perform transactions across various nodes in a blockchain network after a mutual consensus of all the associated nodes in the network. Noticeably, Blockchain is made famous by the Bitcoin cryptocurrency. As of 2017 Blockchain has seen to disrupt many applications to a global worth of 150B. The consensus models are responsible for the process of reaching an agreement between all nodes in blockchain to accept a new block. The consensus model plays a vital role in sustaining Blockchain efficiency. Using the right consensus model can significantly increase the performance of blockchain operation. The consensus models can be divided into two categories. The first category is the proof-based consensus model whereby a node in the Blockchain performs enough proof over other nodes to gain a chance to append the next block to the chain. The second category is the voting-based model in which nodes need to share their results in verifying a transaction of a new block before a final decision is reached. In this paper we discuss the characteristics of some major existing consensus models and provide some critical reviews on their performances. The reviewis mainly concerning these aspects: transaction throughput, latency, network bandwidth, and storage.
{"title":"A Critical Review of Blockchain Consensus Model","authors":"Dodo Khan, L. T. Jung, Manzoor Ahmed Hashmani, A. Waqas","doi":"10.1109/iCoMET48670.2020.9074107","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9074107","url":null,"abstract":"The state-of-art Blockchain technology has been receiving enormous attention from researchers and industry practitioners in recent years. Basically Blockchain is a distributed immutable ledgerutilized by user mainly to perform transactions across various nodes in a blockchain network after a mutual consensus of all the associated nodes in the network. Noticeably, Blockchain is made famous by the Bitcoin cryptocurrency. As of 2017 Blockchain has seen to disrupt many applications to a global worth of 150B. The consensus models are responsible for the process of reaching an agreement between all nodes in blockchain to accept a new block. The consensus model plays a vital role in sustaining Blockchain efficiency. Using the right consensus model can significantly increase the performance of blockchain operation. The consensus models can be divided into two categories. The first category is the proof-based consensus model whereby a node in the Blockchain performs enough proof over other nodes to gain a chance to append the next block to the chain. The second category is the voting-based model in which nodes need to share their results in verifying a transaction of a new block before a final decision is reached. In this paper we discuss the characteristics of some major existing consensus models and provide some critical reviews on their performances. The reviewis mainly concerning these aspects: transaction throughput, latency, network bandwidth, and storage.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125897345","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9073916
A. Abbas, Safdar Nawaz Khan Marwat, Salman Ahmed, Abdul Hafeez, Khalil Ullah, Ihsan Ullah Khan
The information technology’s new revolution is Internet of Things (IoT), where physical world is connected to the internet. IoT applications are diversified such as smart health, smart industry, smart homes and most importantly smart logistics for perishable items conservation. Although IoT devices have revolutionized world but due to their constrained nature they are at the cost of a greater risk of personal data loss, security breaches and misuse. In this research, a review is presented for proposing two state of the art modules i.e. communication model of smart logistics and security of IoT devices in Smart Logistics. As the smart logistics have perishable items i.e. fruits, vegetables, meat, medicine, chemicals, and cosmetics etc. which are sensitive to temperature, humidity and pressure etc. If the sensors monitoring these items have been handled abnormally due to security attacks, it will give huge loss. Therefore, security of smart logistics is of paramount importance in this research. In order to expedite research in this emergent area of IoT, in this research paper a brief review on progress of IoT in smart logistics, and its security has been presented.
{"title":"Proposing Model for Security of IoT Devices in Smart Logistics: A Review","authors":"A. Abbas, Safdar Nawaz Khan Marwat, Salman Ahmed, Abdul Hafeez, Khalil Ullah, Ihsan Ullah Khan","doi":"10.1109/iCoMET48670.2020.9073916","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9073916","url":null,"abstract":"The information technology’s new revolution is Internet of Things (IoT), where physical world is connected to the internet. IoT applications are diversified such as smart health, smart industry, smart homes and most importantly smart logistics for perishable items conservation. Although IoT devices have revolutionized world but due to their constrained nature they are at the cost of a greater risk of personal data loss, security breaches and misuse. In this research, a review is presented for proposing two state of the art modules i.e. communication model of smart logistics and security of IoT devices in Smart Logistics. As the smart logistics have perishable items i.e. fruits, vegetables, meat, medicine, chemicals, and cosmetics etc. which are sensitive to temperature, humidity and pressure etc. If the sensors monitoring these items have been handled abnormally due to security attacks, it will give huge loss. Therefore, security of smart logistics is of paramount importance in this research. In order to expedite research in this emergent area of IoT, in this research paper a brief review on progress of IoT in smart logistics, and its security has been presented.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"78 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131607566","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9074110
R. Khan, Gul Bahar Chachar, I. A. Abro
The purpose of the study was to check how students of grade VIII in Urban Sindh, Pakistan performed on mathematics subject based on Trends in International Mathematics and Science Study (TIMSS) assessment framework. The study used a descriptive design from quantitative research methods. The data were collected from three different educational sectors of urban Sindh. The study used a mathematics test based on the TIMSS framework and 60 items (44 MCQs & 16 CRQs) were adapted from released items. Purposive sampling was used to select the schools (n=6) and random sampling was followed to recruit the research participants (n=180) from grade VIII. There were 38% female and 62% of male research participants. The data were analyzed using descriptive statistical analyses technique. The results indicate that the research participant’s average score is below 30%, indicating an overall low performance of all schools in mathematics tests based on the TIMSS 2011 assessment framework. Some important recommendations for reducing the gap between the proposed and the achieved expertise level in mathematics are given.
{"title":"Mathematics Achievement of Grade VIII Students Based on International Standardized Test (TIMSS) in an Urban Context of Sindh, Pakistan","authors":"R. Khan, Gul Bahar Chachar, I. A. Abro","doi":"10.1109/iCoMET48670.2020.9074110","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9074110","url":null,"abstract":"The purpose of the study was to check how students of grade VIII in Urban Sindh, Pakistan performed on mathematics subject based on Trends in International Mathematics and Science Study (TIMSS) assessment framework. The study used a descriptive design from quantitative research methods. The data were collected from three different educational sectors of urban Sindh. The study used a mathematics test based on the TIMSS framework and 60 items (44 MCQs & 16 CRQs) were adapted from released items. Purposive sampling was used to select the schools (n=6) and random sampling was followed to recruit the research participants (n=180) from grade VIII. There were 38% female and 62% of male research participants. The data were analyzed using descriptive statistical analyses technique. The results indicate that the research participant’s average score is below 30%, indicating an overall low performance of all schools in mathematics tests based on the TIMSS 2011 assessment framework. Some important recommendations for reducing the gap between the proposed and the achieved expertise level in mathematics are given.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115766037","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9073849
Waseem Ahmed, R. Memon, Abdul Fatah Abbasi
Industrialization plays major role in economic development and it is growing very rapidly to fulfil the requirements of resident by increasing production. However, creating financial advantages is no longer the sole goal of industrial growth in the present worldwide sustainable industrial development trend due to the depletion of ozone layer, eco system destruction and changed weather phenomena severely. Nowadays, increasing importance is given on the idea of compatible and continuous economic, ecological and social growth, and the use of eco-efficiency to assess the relationship among the environment influence and economic cost and Eco-industrial Park (EIP) is the solution of dropping environmental problems and promoting financial interests through the interchange of products and energy between sectors for mutual benefit. Thus, the main purpose of this research is to model an Eco-Industrial park in Sindh region in order to find the feasibility as well as cost savings benefits. To achieve this firstly, the literature review and field survey is carried out to identify the potential industries, which are suitable for establishing an Eco - Industrial park. Secondly, the data of wastes/by-products of these industries are determined, after that the model is prepared to show the material flow between the waste producing and utilizing industries. Finally, the possible utilization of these wastes/byproducts is worked out. It is estimated that the coal power plant produces 2273 tons of fly-ash, 239.9 tons of bottom ash and 300 tons of gypsum every day. Thus, utilizing these wastes/byproducts will save around Rs. 2.27 million daily.
{"title":"Development of Eco-Industrial Park in Sindh, Pakistan","authors":"Waseem Ahmed, R. Memon, Abdul Fatah Abbasi","doi":"10.1109/iCoMET48670.2020.9073849","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9073849","url":null,"abstract":"Industrialization plays major role in economic development and it is growing very rapidly to fulfil the requirements of resident by increasing production. However, creating financial advantages is no longer the sole goal of industrial growth in the present worldwide sustainable industrial development trend due to the depletion of ozone layer, eco system destruction and changed weather phenomena severely. Nowadays, increasing importance is given on the idea of compatible and continuous economic, ecological and social growth, and the use of eco-efficiency to assess the relationship among the environment influence and economic cost and Eco-industrial Park (EIP) is the solution of dropping environmental problems and promoting financial interests through the interchange of products and energy between sectors for mutual benefit. Thus, the main purpose of this research is to model an Eco-Industrial park in Sindh region in order to find the feasibility as well as cost savings benefits. To achieve this firstly, the literature review and field survey is carried out to identify the potential industries, which are suitable for establishing an Eco - Industrial park. Secondly, the data of wastes/by-products of these industries are determined, after that the model is prepared to show the material flow between the waste producing and utilizing industries. Finally, the possible utilization of these wastes/byproducts is worked out. It is estimated that the coal power plant produces 2273 tons of fly-ash, 239.9 tons of bottom ash and 300 tons of gypsum every day. Thus, utilizing these wastes/byproducts will save around Rs. 2.27 million daily.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"483 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124497744","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9074065
Naveed Ahmed, N. Ram, A. Memon, Salman Ahmed
Electrical losses and capital cost are two important factors for an efficient transmission of electrical power from generation station to load center. High Voltage Direct Current (HVDC) for its high power carrying capacity is the most suitable option to transmit electrical power leading to low electrical losses and capital cost of the system. However, there is possibility of severe AC and DC faults because of its high power transmission capacity. Fault penetration is more severe in HVDC system due to the power electronics based converters and proper protection is required for the power converters and HVDC transformers owing to their high capital cost. In this work, a simple time-frequency analysis technique is proposed for the identification of HVDC faults using MATLAB/Simulink software. The simulation results show that the most efficient mother Wavelet Transform (WT) based on the standard deviation occurs at the 6th level of decomposition of fault signal to detect the DC fault, symmetrical and asymmetrical faults.
{"title":"Comparative Analysis of Fault Detection for HVDC Transmission System Using Wavelet Transform Based on Standard Deviation","authors":"Naveed Ahmed, N. Ram, A. Memon, Salman Ahmed","doi":"10.1109/iCoMET48670.2020.9074065","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9074065","url":null,"abstract":"Electrical losses and capital cost are two important factors for an efficient transmission of electrical power from generation station to load center. High Voltage Direct Current (HVDC) for its high power carrying capacity is the most suitable option to transmit electrical power leading to low electrical losses and capital cost of the system. However, there is possibility of severe AC and DC faults because of its high power transmission capacity. Fault penetration is more severe in HVDC system due to the power electronics based converters and proper protection is required for the power converters and HVDC transformers owing to their high capital cost. In this work, a simple time-frequency analysis technique is proposed for the identification of HVDC faults using MATLAB/Simulink software. The simulation results show that the most efficient mother Wavelet Transform (WT) based on the standard deviation occurs at the 6th level of decomposition of fault signal to detect the DC fault, symmetrical and asymmetrical faults.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121324647","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9073851
W. Uddin, M. Ishfaq, K. Zeb, S. Islam, Hee Je Kim, M. Khan, Z. Ullah, I. Khan, Khadim Ullah Jan, Muhammad Asim Sarwar
Modular Multilevel Converter (MMC) is very popular due to its flexibility, use of low rating devices, low harmonic distortion, and high efficiency. Despite these advantages, MMC faces challenges of controlling its parameters especially inner current and capacitor voltages. This paper presents the control of the inner current of MMC using Sliding Mode Controller (SMC). The switching function of SMC is based on 2nd order super twisting algorithm. The Proposed super twisting algorithm is proved to be efficient in controlling the inner current. The 2nd order harmonic is effectively suppressed, and the inner current is fully converged to its reference value. Moreover, the continuous nature of the super twisting algorithm solves the chattering issue. The implementation of MMC and its control is carried out in MATLAB/Simulink.
{"title":"Super twisting sliding mode control for inner current suppression of Modular Multilevel Converter","authors":"W. Uddin, M. Ishfaq, K. Zeb, S. Islam, Hee Je Kim, M. Khan, Z. Ullah, I. Khan, Khadim Ullah Jan, Muhammad Asim Sarwar","doi":"10.1109/iCoMET48670.2020.9073851","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9073851","url":null,"abstract":"Modular Multilevel Converter (MMC) is very popular due to its flexibility, use of low rating devices, low harmonic distortion, and high efficiency. Despite these advantages, MMC faces challenges of controlling its parameters especially inner current and capacitor voltages. This paper presents the control of the inner current of MMC using Sliding Mode Controller (SMC). The switching function of SMC is based on 2nd order super twisting algorithm. The Proposed super twisting algorithm is proved to be efficient in controlling the inner current. The 2nd order harmonic is effectively suppressed, and the inner current is fully converged to its reference value. Moreover, the continuous nature of the super twisting algorithm solves the chattering issue. The implementation of MMC and its control is carried out in MATLAB/Simulink.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"1620 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121719232","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9074141
Abdul Rauf Memon, Saadia Kulsoom Memon, A. Memon, Tayab Din Memon
Internet of things (IoT) is relatively a new paradigm in the area of information and technology. It aims at making life easier and more comfortable by providing easy ways and mechanisms to handle day to day tasks effectively. In recent years, the pollution especially water pollution has become one of the major issues that is faced by countries around the world. The increase of amount of factory and vehicle had caused the emission of plague water and chemical to the river, sea and pond. Hence, it is important to monitor the water quality constantly so that immediate action can be taken to counter water pollution. Water quality is described as the general composition of water with reference to its chemical, physical, and biological properties. Water is a limited natural resource and it is very essential for human beings. The purpose of this research was to make an IoT based cost effective system that can monitor the quality of water in real time. The design and implementation of the system is done with the help of WeMos D1 mini and sensors (pH, turbidity, temperature and ultrasonic). WeMos D1 mini is an Arduino like board with built in Wi-Fi capabilities to send sensors data over the internet. The overall experimental setup was developed and tested for water quality data acquisition, online data transfer, monitoring, recording and analysis. It is experimentally observed that system takes less than a minute to update its values. This costeffective system is very beneficial for resident as well as for industries to monitor the water quality.
{"title":"IoT Based Water Quality Monitoring System for Safe Drinking Water in Pakistan","authors":"Abdul Rauf Memon, Saadia Kulsoom Memon, A. Memon, Tayab Din Memon","doi":"10.1109/iCoMET48670.2020.9074141","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9074141","url":null,"abstract":"Internet of things (IoT) is relatively a new paradigm in the area of information and technology. It aims at making life easier and more comfortable by providing easy ways and mechanisms to handle day to day tasks effectively. In recent years, the pollution especially water pollution has become one of the major issues that is faced by countries around the world. The increase of amount of factory and vehicle had caused the emission of plague water and chemical to the river, sea and pond. Hence, it is important to monitor the water quality constantly so that immediate action can be taken to counter water pollution. Water quality is described as the general composition of water with reference to its chemical, physical, and biological properties. Water is a limited natural resource and it is very essential for human beings. The purpose of this research was to make an IoT based cost effective system that can monitor the quality of water in real time. The design and implementation of the system is done with the help of WeMos D1 mini and sensors (pH, turbidity, temperature and ultrasonic). WeMos D1 mini is an Arduino like board with built in Wi-Fi capabilities to send sensors data over the internet. The overall experimental setup was developed and tested for water quality data acquisition, online data transfer, monitoring, recording and analysis. It is experimentally observed that system takes less than a minute to update its values. This costeffective system is very beneficial for resident as well as for industries to monitor the water quality.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126062703","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9073799
Umer Asgher, Khurram Khalil, Y. Ayaz, Riaz Ahmad, Muhammad Jawad Khan
In the current era of technological advancements and rising human-machine interaction, urged the vital importance of human factors and ergonomics in an industrial collaborative environment. These ergonomic needs have made it essential to analyze the industrial cognitive processes like mental workload (MWL), stress and vigilance in the ecological environment. Conventionally Electroencephalography (EEG) was used for assessment of brain electrical activity but recently functional Near-Infrared Spectroscopy (fNIRS) has immerged as a better substitute for acquiring brain signals with fewer protocols and enhanced spatial resolution. Over the period of time Machine learning algorithms (LDA, k-NN, ANN) are used to classify MWL and affiliated brain functions. Now the trend of employing Deep learning techniques is gaining popularity. In this study, we analyzed and classified MWL states using Machine learning (SVM) and Deep learning (CNN) algorithms. The classification accuracies achieved with Deep learning (CNN) outperformed the accuracies achieved with Machine learning algorithms. The best accuracies were achieved using CNN that are in the range of 80-87%. Finally, a comparison is drawn between Machine learning and Deep learning algorithms for better classification and discrimination of cognitive loads.
{"title":"Classification of Mental Workload (MWL) using Support Vector Machines (SVM) and Convolutional Neural Networks (CNN)","authors":"Umer Asgher, Khurram Khalil, Y. Ayaz, Riaz Ahmad, Muhammad Jawad Khan","doi":"10.1109/iCoMET48670.2020.9073799","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9073799","url":null,"abstract":"In the current era of technological advancements and rising human-machine interaction, urged the vital importance of human factors and ergonomics in an industrial collaborative environment. These ergonomic needs have made it essential to analyze the industrial cognitive processes like mental workload (MWL), stress and vigilance in the ecological environment. Conventionally Electroencephalography (EEG) was used for assessment of brain electrical activity but recently functional Near-Infrared Spectroscopy (fNIRS) has immerged as a better substitute for acquiring brain signals with fewer protocols and enhanced spatial resolution. Over the period of time Machine learning algorithms (LDA, k-NN, ANN) are used to classify MWL and affiliated brain functions. Now the trend of employing Deep learning techniques is gaining popularity. In this study, we analyzed and classified MWL states using Machine learning (SVM) and Deep learning (CNN) algorithms. The classification accuracies achieved with Deep learning (CNN) outperformed the accuracies achieved with Machine learning algorithms. The best accuracies were achieved using CNN that are in the range of 80-87%. Finally, a comparison is drawn between Machine learning and Deep learning algorithms for better classification and discrimination of cognitive loads.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127618098","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9073938
A. Rehman, M. A. Qyyum, Fatima Zakir, Saad Nawaz, Xiufen He, L. Razzaq, Moonyong Lee, Li Wang
Keeping in view recent energy challenges, natural gas (NG) and other associated fuels such as liquefied petroleum gas (LPG) have been taken into account being clean sources of energy as compared with oil and coal. Due to economic infeasibility of NG transportation through pipelines, liquefied natural gas (LNG) is considered as a promising eco-friendly candidate to transport natural gas to remote locations around the globe. However, the NG liquefaction is an energy and cost-intensive process mainly because of large amount of energy consumption by compression units taking part in liquefaction process. In this study, newly developed modified single mixed refrigerant (MSMR) process was utilized to liquefy NG which is specially targeted for offshore application. To examine the real potential for improvements in MSMR process, the sources of irreversibilities are identified using advanced exergy analysis (AEA). Conventional exergy analysis (CEA) on MSMR LNG process was applied to evaluate the exergy destruction through involved components. Keeping in view to compute potential of improvement in the whole process, destruction of exergy of the process was divided into unavoidable and avoidable sections. Unavoidable part of total exergy destruction was observed only 42% which was less than avoidable portion leading the analyzer to gauge the real potential of improvement. Composite curves analysis was also carried through to analyze the heat transfer efficiency and overall performance of cryogenic heat exchangers involved in the MSMR process.
{"title":"Investigation of improvement potential of Modified Single Mixed Refrigerant (MSMR) LNG process in terms of avoidable and unavoidable exergy destruction","authors":"A. Rehman, M. A. Qyyum, Fatima Zakir, Saad Nawaz, Xiufen He, L. Razzaq, Moonyong Lee, Li Wang","doi":"10.1109/iCoMET48670.2020.9073938","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9073938","url":null,"abstract":"Keeping in view recent energy challenges, natural gas (NG) and other associated fuels such as liquefied petroleum gas (LPG) have been taken into account being clean sources of energy as compared with oil and coal. Due to economic infeasibility of NG transportation through pipelines, liquefied natural gas (LNG) is considered as a promising eco-friendly candidate to transport natural gas to remote locations around the globe. However, the NG liquefaction is an energy and cost-intensive process mainly because of large amount of energy consumption by compression units taking part in liquefaction process. In this study, newly developed modified single mixed refrigerant (MSMR) process was utilized to liquefy NG which is specially targeted for offshore application. To examine the real potential for improvements in MSMR process, the sources of irreversibilities are identified using advanced exergy analysis (AEA). Conventional exergy analysis (CEA) on MSMR LNG process was applied to evaluate the exergy destruction through involved components. Keeping in view to compute potential of improvement in the whole process, destruction of exergy of the process was divided into unavoidable and avoidable sections. Unavoidable part of total exergy destruction was observed only 42% which was less than avoidable portion leading the analyzer to gauge the real potential of improvement. Composite curves analysis was also carried through to analyze the heat transfer efficiency and overall performance of cryogenic heat exchangers involved in the MSMR process.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127347769","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 : 2020-01-01DOI: 10.1109/iCoMET48670.2020.9074069
Asif Ali, Shahnawaz Talpur, Sanam Narejo
In today’s era, data is stored for later analysis but most of the significant applications such as WSN, and Medical Science are producing uncertain data. Still, the recorded uncertain data can be analyzed to produce probabilistic answers but the conventional DBMS are designed based on First Order Logic so they are unable to store and process data with some uncertainty or missing values. At the same time, it is not beneficial to delete uncertain data it may affect the result. To deal with uncertain data, Different research groups at the world's renowned institutes developed the Probabilistic DBMS. Like a research group at Oxford University has developed the MayBMS: A probabilistic database management system to analyze the uncertain data. But before using the probabilistic DBMS to manage the uncertain data, the uncertainty in the data should be calculated using probability theory to know the correctness of each record. The purpose of writing this research paper is to find a way to measure the uncertainty available in the data before managing it. Because the management of uncertain data is the second phase, the first thing is to know the correctness or falseness of each available record in the dataset.
{"title":"Detecting Faulty Sensors by Analyzing the Uncertain Data Using Probabilistic Database","authors":"Asif Ali, Shahnawaz Talpur, Sanam Narejo","doi":"10.1109/iCoMET48670.2020.9074069","DOIUrl":"https://doi.org/10.1109/iCoMET48670.2020.9074069","url":null,"abstract":"In today’s era, data is stored for later analysis but most of the significant applications such as WSN, and Medical Science are producing uncertain data. Still, the recorded uncertain data can be analyzed to produce probabilistic answers but the conventional DBMS are designed based on First Order Logic so they are unable to store and process data with some uncertainty or missing values. At the same time, it is not beneficial to delete uncertain data it may affect the result. To deal with uncertain data, Different research groups at the world's renowned institutes developed the Probabilistic DBMS. Like a research group at Oxford University has developed the MayBMS: A probabilistic database management system to analyze the uncertain data. But before using the probabilistic DBMS to manage the uncertain data, the uncertainty in the data should be calculated using probability theory to know the correctness of each record. The purpose of writing this research paper is to find a way to measure the uncertainty available in the data before managing it. Because the management of uncertain data is the second phase, the first thing is to know the correctness or falseness of each available record in the dataset.","PeriodicalId":431051,"journal":{"name":"2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)","volume":"21 S4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114046800","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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