Pub Date : 2023-11-08DOI: 10.37256/jeee.2220233390
Alireza Hamedi, Dariush Keihan Asl, Ali Reza Seifi
In this paper, a village energy system is coupled with the wide-area energy network based on the energy hub concept. The village is modeled as an isolated energy hub while it could interact with the energy sub-networks including the electrical, and natural gas through the market. The energy demand of village is supplied with renewable resources such as photovoltaic (PV) system and other generation such as combined heat and power (CHP) technologies. The CHP unit is modeled by the part-load performance. In addition, the battery energy storage is presented beside the PV system to damp the intermittent generation of PV and to be utilized in the high prices of the market. The optimal operation problem is solved to maximize the profit from the energy hub operator point of view. The optimization problem is solved with the teaching-learning based optimization (TLBO) method. The results show that the proper interaction of the village energy system with the upstream sub-networks is so affordable for the system operator to increase the profit, in a way that the maximum benefit of village energy system is reached to 3.6456$.
{"title":"Optimal Operation of a Village Energy System Considering Renewable Resources and Battery Energy Storage","authors":"Alireza Hamedi, Dariush Keihan Asl, Ali Reza Seifi","doi":"10.37256/jeee.2220233390","DOIUrl":"https://doi.org/10.37256/jeee.2220233390","url":null,"abstract":"In this paper, a village energy system is coupled with the wide-area energy network based on the energy hub concept. The village is modeled as an isolated energy hub while it could interact with the energy sub-networks including the electrical, and natural gas through the market. The energy demand of village is supplied with renewable resources such as photovoltaic (PV) system and other generation such as combined heat and power (CHP) technologies. The CHP unit is modeled by the part-load performance. In addition, the battery energy storage is presented beside the PV system to damp the intermittent generation of PV and to be utilized in the high prices of the market. The optimal operation problem is solved to maximize the profit from the energy hub operator point of view. The optimization problem is solved with the teaching-learning based optimization (TLBO) method. The results show that the proper interaction of the village energy system with the upstream sub-networks is so affordable for the system operator to increase the profit, in a way that the maximum benefit of village energy system is reached to 3.6456$.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391496","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 : 2023-11-07DOI: 10.37256/jeee.2220233411
José M. Campos-Salazar, Pablo Lecaros, Rodrigo Sandoval
This comprehensive research addresses a gap in the literature by providing an extensive examination of a single-component single-stage vaporizer process. The research involves sophisticated analyses such as dynamic modeling, comprehensive control system design and performance evaluation. The study systematically derives a linear state-space model from complex nonlinear dynamic models, laying the basis for the development of two highly effective control systems specifically designed for vaporizer level and temperature control. The simulations of these control structures demonstrate notable properties, including fast disturbance rejection, minimal overshoot, and virtually no steady-state error, emphasizing their robustness and precision. This research focuses on the stability and response of the system and provides insight into its transient behavior during disturbances and setpoint changes. The study's broad implications extend beyond the results and provide a path for future improvements. The results indicate ways to refine the start-up stage, minimize initial overshoot during system initialization, and further improve control strategies. This work has the potential to make a difference in advancing the field of vaporization processes, providing engineers and researchers with the tools and insights needed to improve system reliability and performance in industrial applications.
{"title":"Cascade Control Applied to a Single-Component Single-Stage Vaporizer—Modeling and Simulation","authors":"José M. Campos-Salazar, Pablo Lecaros, Rodrigo Sandoval","doi":"10.37256/jeee.2220233411","DOIUrl":"https://doi.org/10.37256/jeee.2220233411","url":null,"abstract":"This comprehensive research addresses a gap in the literature by providing an extensive examination of a single-component single-stage vaporizer process. The research involves sophisticated analyses such as dynamic modeling, comprehensive control system design and performance evaluation. The study systematically derives a linear state-space model from complex nonlinear dynamic models, laying the basis for the development of two highly effective control systems specifically designed for vaporizer level and temperature control. The simulations of these control structures demonstrate notable properties, including fast disturbance rejection, minimal overshoot, and virtually no steady-state error, emphasizing their robustness and precision. This research focuses on the stability and response of the system and provides insight into its transient behavior during disturbances and setpoint changes. The study's broad implications extend beyond the results and provide a path for future improvements. The results indicate ways to refine the start-up stage, minimize initial overshoot during system initialization, and further improve control strategies. This work has the potential to make a difference in advancing the field of vaporization processes, providing engineers and researchers with the tools and insights needed to improve system reliability and performance in industrial applications.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135432089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-20DOI: 10.37256/jeee.2220233418
Alberto Coboi, Minh T. Nguyen, Kien T. La, Thang C. Vu
This paper presents a ZigBee-based wireless network gas monitoring system, utilizing ZigBee technology to enable reliable and low-cost communication. The system leverages small sensor nodes and ZigBee protocols to collect data on physical phenomena, particularly gas levels, in various environments. The network's low-power consumption and extended range capabilities allow for effective gas sensing within a radius of up to 300 meters. While interoperability with devices from different manufacturers remains a limitation, the system showcases the versatility of ZigBee technology in diverse fields. The study evaluates the system's performance through simulation and experimentation, addresses potential challenges, and proposes future developments to enhance ZigBee-based wireless network gas monitoring systems, offering improved remote monitoring and manipulation capabilities. Furthermore, our research contributes to the advancement of wireless sensor network technology by demonstrating the practicality of ZigBee in gas monitoring. The findings from our experiments and simulations provide valuable insights into the optimization of such systems, which can have far-reaching impacts on environmental monitoring, safety, and industrial processes. In addition, our proposed enhancements pave the way for more reliable and efficient remote monitoring and control, offering substantial benefits for various industries, including environmental management, industrial automation, and beyond.
{"title":"Wireless Sensor Network Based Gas Monitoring System Utilizing ZigBee Technology","authors":"Alberto Coboi, Minh T. Nguyen, Kien T. La, Thang C. Vu","doi":"10.37256/jeee.2220233418","DOIUrl":"https://doi.org/10.37256/jeee.2220233418","url":null,"abstract":"This paper presents a ZigBee-based wireless network gas monitoring system, utilizing ZigBee technology to enable reliable and low-cost communication. The system leverages small sensor nodes and ZigBee protocols to collect data on physical phenomena, particularly gas levels, in various environments. The network's low-power consumption and extended range capabilities allow for effective gas sensing within a radius of up to 300 meters. While interoperability with devices from different manufacturers remains a limitation, the system showcases the versatility of ZigBee technology in diverse fields. The study evaluates the system's performance through simulation and experimentation, addresses potential challenges, and proposes future developments to enhance ZigBee-based wireless network gas monitoring systems, offering improved remote monitoring and manipulation capabilities. Furthermore, our research contributes to the advancement of wireless sensor network technology by demonstrating the practicality of ZigBee in gas monitoring. The findings from our experiments and simulations provide valuable insights into the optimization of such systems, which can have far-reaching impacts on environmental monitoring, safety, and industrial processes. In addition, our proposed enhancements pave the way for more reliable and efficient remote monitoring and control, offering substantial benefits for various industries, including environmental management, industrial automation, and beyond.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135567793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-07DOI: 10.37256/jeee.2220233484
Mohammad Yousefzadeh, Hussein Eliasi, Morteza Jalilirad
The permanent magnet synchronous motor (PMSM) is mathematically modeled and simulated in this study using MATLAB. PMSM is a nonlinear, multi-variable and time-varying system and due to nonlinearities and its strong coupling between its variables, the dynamical behaviour of the PMSM is complex. Therefore, under specified parameters and conditions, chaotic undesirable phenomenon arise in the PMSM. For a chaotic PMSM drive system, this paper proposes a sliding mode control (SMC) approach based on the Lyapunov stability theory to control and suppress the chaotic motion emergence. Firstly, the dynamic characteristics of the state equations of the PMSM drive system is analysed and demonstrated that it will appear chaos phenomenon at some certain parameters. Finally, the SMC strategy and Lyapunov stability theory are combined to introduce a sliding surface and produce a control rule. Simulation results are presented to verify that the proposed strategy can be successfully employed to control a chaotic PMSM and make the system asymptotically stable to the equilibrium point.
{"title":"Dynamic Modeling and Chaos Suppression of the Permanent Magnet Synchronous Motor Drive with Sliding Mode Control","authors":"Mohammad Yousefzadeh, Hussein Eliasi, Morteza Jalilirad","doi":"10.37256/jeee.2220233484","DOIUrl":"https://doi.org/10.37256/jeee.2220233484","url":null,"abstract":"The permanent magnet synchronous motor (PMSM) is mathematically modeled and simulated in this study using MATLAB. PMSM is a nonlinear, multi-variable and time-varying system and due to nonlinearities and its strong coupling between its variables, the dynamical behaviour of the PMSM is complex. Therefore, under specified parameters and conditions, chaotic undesirable phenomenon arise in the PMSM. For a chaotic PMSM drive system, this paper proposes a sliding mode control (SMC) approach based on the Lyapunov stability theory to control and suppress the chaotic motion emergence. Firstly, the dynamic characteristics of the state equations of the PMSM drive system is analysed and demonstrated that it will appear chaos phenomenon at some certain parameters. Finally, the SMC strategy and Lyapunov stability theory are combined to introduce a sliding surface and produce a control rule. Simulation results are presented to verify that the proposed strategy can be successfully employed to control a chaotic PMSM and make the system asymptotically stable to the equilibrium point.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135254977","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 : 2023-09-29DOI: 10.37256/jeee.2220233421
Marcelo Delgado-del-Carpio, A. Hilario-Tacuri, Carlos A. Hernández-Gutiérrez
This work presents the design of a microprocessor synthesized in FPGA based on the IEC 61131-3 standard. We report the architecture, and the operation of the internal hardware which allows the execution of Instruction List (IL). One of the most important components is the operands_selector block which allows memory elements, inputs, or outputs of the microprocessor to be treated as operands. Two ALUs are available to perform a bit, integer, and floating-point operations. The implementation of this microprocessor allows concluding that our designed microprocessor implemented in xc7a100tcsg324 (Xilinx) or EP4CE10E22C8 (Intel) FPGAs is superior in their execution times compared to the microprocessor evaluated in early studies and to one of the S7-1500 family processor.
{"title":"Modeling and Implementation of a Specific Microprocessor to Enhance the Performance of PLCs Employing FPGAs","authors":"Marcelo Delgado-del-Carpio, A. Hilario-Tacuri, Carlos A. Hernández-Gutiérrez","doi":"10.37256/jeee.2220233421","DOIUrl":"https://doi.org/10.37256/jeee.2220233421","url":null,"abstract":"This work presents the design of a microprocessor synthesized in FPGA based on the IEC 61131-3 standard. We report the architecture, and the operation of the internal hardware which allows the execution of Instruction List (IL). One of the most important components is the operands_selector block which allows memory elements, inputs, or outputs of the microprocessor to be treated as operands. Two ALUs are available to perform a bit, integer, and floating-point operations. The implementation of this microprocessor allows concluding that our designed microprocessor implemented in xc7a100tcsg324 (Xilinx) or EP4CE10E22C8 (Intel) FPGAs is superior in their execution times compared to the microprocessor evaluated in early studies and to one of the S7-1500 family processor.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135199628","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}
This research proposes a machine learning-based attack detection model for power systems, specifically targeting smart grids. By utilizing data and logs collected from Phasor Measuring Devices (PMUs), the model aims to learn system behaviors and effectively identify potential security boundaries. The proposed approach involves crucial stages including dataset preprocessing, feature selection, model creation, and evaluation. To validate our approach, we used a dataset used, consist of 15 separate datasets obtained from different PMUs, relay snort alarms and logs. Three machine learning models: Random Forest, Logistic Regression, and K-Nearest Neighbour were built and evaluated using various performance metrics. The findings indicate that the Random Forest model achieves the highest performance with an accuracy of 90.56% in detecting power system disturbances and has the potential in assisting operators in decision-making processes
{"title":"Machine Learning to Detect Cyber-Attacks and Discriminating the Types of Power System Disturbances","authors":"","doi":"10.33140/jeee.02.03.17","DOIUrl":"https://doi.org/10.33140/jeee.02.03.17","url":null,"abstract":"This research proposes a machine learning-based attack detection model for power systems, specifically targeting smart grids. By utilizing data and logs collected from Phasor Measuring Devices (PMUs), the model aims to learn system behaviors and effectively identify potential security boundaries. The proposed approach involves crucial stages including dataset preprocessing, feature selection, model creation, and evaluation. To validate our approach, we used a dataset used, consist of 15 separate datasets obtained from different PMUs, relay snort alarms and logs. Three machine learning models: Random Forest, Logistic Regression, and K-Nearest Neighbour were built and evaluated using various performance metrics. The findings indicate that the Random Forest model achieves the highest performance with an accuracy of 90.56% in detecting power system disturbances and has the potential in assisting operators in decision-making processes","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135471783","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}
Renewable energy sources like solar panels and wind turbines are becoming more important for generating power. The inconsistent and unreliable output of solar panels and wind turbines is due to factors like clouds, weather conditions, and wind speed that cause their energy production to fluctuate. Connecting intermittent sources to the utility grid creates difficulties in different technical areas, such as ensuring a steady and reliable power supply, protecting the system from disruptions, controlling the distribution of generated power, and maintaining a consistent level of power quality. In this situation, adjusting the amount of electricity produced by an intermittent energy source to keep the power grid stable is essential. This issue must be resolved as soon as possible. The extension to these locations diminishes the grid's strength. It leads to a scenario where a solar power plant is integrated into a subpar electric grid. However, integrating solar power into a shoddy AC infrastructure has problems with power quality (PQ) problems, which restricts penetration levels. This review article suggests various FACTS devices and various conventional, adaptive, and AI-based algorithms to reduce PQ issues brought on by a weak grid and increase renewable energy source (RES) penetration levels. This paper discusses the PQ issues that occur when RES like solar power plants (SPP) and wind power plants (WPP) or both as hybrid are connected to the electrical grid. It also explores different ways to reduce the fluctuation in power output from the solar panels. It analyzes the numerous power quality issues that arise with solar penetration and PQ mitigation methods using several FACTS devices and control algorithms, including traditional control, adaptive control, and AI-based control algorithms. For the benefit of engineers and academics working in this field of study, various research publications have been carefully evaluated, organized, and placed on this paper for convenient reference. It also briefly discusses the plan for controlling battery storage system for solve this problem.
{"title":"A Comprehensive Review: Mitigating Techniques for Power Variability Due to Integration of Renewable Energy Sources With Grid","authors":"Virendra Sharma, Preeti Garg, Ajay Sharma, Nishant Bharti","doi":"10.37256/jeee.2220233380","DOIUrl":"https://doi.org/10.37256/jeee.2220233380","url":null,"abstract":"Renewable energy sources like solar panels and wind turbines are becoming more important for generating power. The inconsistent and unreliable output of solar panels and wind turbines is due to factors like clouds, weather conditions, and wind speed that cause their energy production to fluctuate. Connecting intermittent sources to the utility grid creates difficulties in different technical areas, such as ensuring a steady and reliable power supply, protecting the system from disruptions, controlling the distribution of generated power, and maintaining a consistent level of power quality. In this situation, adjusting the amount of electricity produced by an intermittent energy source to keep the power grid stable is essential. This issue must be resolved as soon as possible. The extension to these locations diminishes the grid's strength. It leads to a scenario where a solar power plant is integrated into a subpar electric grid. However, integrating solar power into a shoddy AC infrastructure has problems with power quality (PQ) problems, which restricts penetration levels. This review article suggests various FACTS devices and various conventional, adaptive, and AI-based algorithms to reduce PQ issues brought on by a weak grid and increase renewable energy source (RES) penetration levels. This paper discusses the PQ issues that occur when RES like solar power plants (SPP) and wind power plants (WPP) or both as hybrid are connected to the electrical grid. It also explores different ways to reduce the fluctuation in power output from the solar panels. It analyzes the numerous power quality issues that arise with solar penetration and PQ mitigation methods using several FACTS devices and control algorithms, including traditional control, adaptive control, and AI-based control algorithms. For the benefit of engineers and academics working in this field of study, various research publications have been carefully evaluated, organized, and placed on this paper for convenient reference. It also briefly discusses the plan for controlling battery storage system for solve this problem.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135477328","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 : 2023-09-26DOI: 10.37256/jeee.2220233266
Mohammed Alsumady, Ibrahim Jaber, Khalid Nusserat
Multilevel inverters (MLIs) are gaining more interest recently in medium to high power applications. The main problem with various MLI topologies is that they require a large number of switching devices and DC voltage sources while producing a small number of voltage levels. Which results in bulky inverters with high cost and high output voltage/current total harmonic distortion (THD). This paper introduces a new novel asymmetrical 17-level MLI design using two DC voltage sources and a reduced number of switches. This was achieved by combining a voltage summing and subtracting circuit with a modified diode clamped MLI (DC-MLI), which divides the voltage by two. Thus, generating more voltage levels. nearest level control (NLC) is used to produce the switching signals at a switching frequency of 50Hz. The design is tested and simulated using MATLAB/Simulink, the output voltage THD is kept around 5.7%. The obtained results are compared with other recent 17-level topologies, showing that a good improvement is achieved.
{"title":"17 Level Hybrid Diode Clamped Inverter With Reduced Number of Components","authors":"Mohammed Alsumady, Ibrahim Jaber, Khalid Nusserat","doi":"10.37256/jeee.2220233266","DOIUrl":"https://doi.org/10.37256/jeee.2220233266","url":null,"abstract":"Multilevel inverters (MLIs) are gaining more interest recently in medium to high power applications. The main problem with various MLI topologies is that they require a large number of switching devices and DC voltage sources while producing a small number of voltage levels. Which results in bulky inverters with high cost and high output voltage/current total harmonic distortion (THD). This paper introduces a new novel asymmetrical 17-level MLI design using two DC voltage sources and a reduced number of switches. This was achieved by combining a voltage summing and subtracting circuit with a modified diode clamped MLI (DC-MLI), which divides the voltage by two. Thus, generating more voltage levels. nearest level control (NLC) is used to produce the switching signals at a switching frequency of 50Hz. The design is tested and simulated using MATLAB/Simulink, the output voltage THD is kept around 5.7%. The obtained results are compared with other recent 17-level topologies, showing that a good improvement is achieved.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134886159","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}
Rhino manometry is widely used for measuring nasal aerodynamic resistance, but its clinical use is still limited and needs further standardization. The main aim of the study is to determine the total nasal resistance and to locate the place and the reasons for nasal cavity obstruction. A scheme of modern hybrid computed Rhino manometry for functional diagnosis of upper respiratory disease is proposed. The role of the main parameters in nasal aerodynamics is described (the airflow, the pressure, different types of local resistances, and nasal respiratory energy efficiency). The hybrid approach is based on a CT study and the Rhino manometry data. The study discovers four new features in the nasal breathing graph, which help in discrimination between different types of breathing modes, and this increases the accuracy of calculating the pressure losses by 12%. Also, the method used for calculating the mucosal roughness, which used as a criterion for evaluating the airflow mode. The accuracy of the hybrid functional method in calculating the total nasal aerodynamic resistance is 30% higher than with previous methods.
{"title":"Nasal Breathing Computed Diagnosis System","authors":"","doi":"10.33140/jeee.02.03.15","DOIUrl":"https://doi.org/10.33140/jeee.02.03.15","url":null,"abstract":"Rhino manometry is widely used for measuring nasal aerodynamic resistance, but its clinical use is still limited and needs further standardization. The main aim of the study is to determine the total nasal resistance and to locate the place and the reasons for nasal cavity obstruction. A scheme of modern hybrid computed Rhino manometry for functional diagnosis of upper respiratory disease is proposed. The role of the main parameters in nasal aerodynamics is described (the airflow, the pressure, different types of local resistances, and nasal respiratory energy efficiency). The hybrid approach is based on a CT study and the Rhino manometry data. The study discovers four new features in the nasal breathing graph, which help in discrimination between different types of breathing modes, and this increases the accuracy of calculating the pressure losses by 12%. Also, the method used for calculating the mucosal roughness, which used as a criterion for evaluating the airflow mode. The accuracy of the hybrid functional method in calculating the total nasal aerodynamic resistance is 30% higher than with previous methods.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136100796","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}
Image captioning is a computer vision task that involves generating natural language descriptions for images. This method has numerous applications in various domains, including image retrieval systems, medicine, and various industries. However, while there has been significant research in image captioning, most studies have focused on high quality images or controlled environments, without exploring the challenges of real-world image captioning. Real-world image captioning involves complex and dynamic environments with numerous points of attention, with images which are often very poor in quality, making it a challenging task, even for humans. This paper evaluates the performance of various models that are built on top of different encoding mechanisms, language decoders and training procedures using a newly created real-world dataset that consists of over 800+ images of over 65 different scene classes, built using MIT Indoor scenes dataset. This dataset is captioned using the IC3 approach that generates more descriptive captions by summarizing the details that are covered by standard image captioning models from unique view-points of the image.
{"title":"A Comprehensive Analysis of Real-World Image Captioning and Scene Identification","authors":"","doi":"10.33140/jeee.02.03.14","DOIUrl":"https://doi.org/10.33140/jeee.02.03.14","url":null,"abstract":"Image captioning is a computer vision task that involves generating natural language descriptions for images. This method has numerous applications in various domains, including image retrieval systems, medicine, and various industries. However, while there has been significant research in image captioning, most studies have focused on high quality images or controlled environments, without exploring the challenges of real-world image captioning. Real-world image captioning involves complex and dynamic environments with numerous points of attention, with images which are often very poor in quality, making it a challenging task, even for humans. This paper evaluates the performance of various models that are built on top of different encoding mechanisms, language decoders and training procedures using a newly created real-world dataset that consists of over 800+ images of over 65 different scene classes, built using MIT Indoor scenes dataset. This dataset is captioned using the IC3 approach that generates more descriptive captions by summarizing the details that are covered by standard image captioning models from unique view-points of the image.","PeriodicalId":39047,"journal":{"name":"Journal of Electrical and Electronics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135110201","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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