Okba Boutebba, S. Semcheddine, F. Krim, B. Talbi, A. Reatti, F. Corti
This paper introduces two improved control algorithms for DC-DC converters. The first one is called “Non-Adaptive Modified Back-Stepping Control” (M-BSC) and the second one is called “Adaptive Modified Back-Stepping Control” (AM-BSC). Both the proposed control schemes allow one to increase the robustness to load and input voltage variations and make the DC-DC converter less sensitive to disturbances concerning the control algorithms available in the literature. The control aims to keep the output voltage at the desired value despite any changes that may occur during its operation. As a case study, the proposed control techniques have been applied to a DC-DC Buck converter. To validate the theoretical results and evaluate the performance of the proposed control algorithms, numerical simulations with four different scenarios have been analyzed: nominal operating conditions, load variations, output voltage tracking, and input voltage variations. The simulation results highlight the good performance of the proposed control algorithms compared to other classical algorithms, improving both the stationary error and the response time.
{"title":"Robust Non-Linear Controller Design for DC-DC Buck Converter via Modified Back-Stepping Methodology","authors":"Okba Boutebba, S. Semcheddine, F. Krim, B. Talbi, A. Reatti, F. Corti","doi":"10.5755/j02.eie.31487","DOIUrl":"https://doi.org/10.5755/j02.eie.31487","url":null,"abstract":"This paper introduces two improved control algorithms for DC-DC converters. The first one is called “Non-Adaptive Modified Back-Stepping Control” (M-BSC) and the second one is called “Adaptive Modified Back-Stepping Control” (AM-BSC). Both the proposed control schemes allow one to increase the robustness to load and input voltage variations and make the DC-DC converter less sensitive to disturbances concerning the control algorithms available in the literature. The control aims to keep the output voltage at the desired value despite any changes that may occur during its operation. As a case study, the proposed control techniques have been applied to a DC-DC Buck converter. To validate the theoretical results and evaluate the performance of the proposed control algorithms, numerical simulations with four different scenarios have been analyzed: nominal operating conditions, load variations, output voltage tracking, and input voltage variations. The simulation results highlight the good performance of the proposed control algorithms compared to other classical algorithms, improving both the stationary error and the response time.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41747070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Shasidharan, S. Mariappan, Li Yizhi, J. Rajendran, Mark Wong
This paper describes the implementation of low-power, low-phase-noise (PN), and robust startup tailless class-C voltage-controlled oscillator (TVCO) for 5G new radio (NR) technology. It features dual gate voltage control source biasing to generate fast startup and differential signal amplitude balancing, thus eliminating the requirement of the conventional tail current source, which introduces more parasitic capacitance that affects the oscillation frequency, phase noise, and power consumption. The TVCO is fabricated in 180 nm complementary metal-oxide semiconductor (CMOS) technology, oscillating at 2.59 GHz 5G NR carrier frequency with an output voltage swing of 1.7 V and low-phase-noise of -122 dBc/Hz at 1 MHz offset with supply voltage headroom of 0.7 V. Without additional features added, the TVCO consumes very low-power and a small die area of 0.98 mW and 0.49 mm2, respectively. The achieved figure of merit (FoM) is 190.36 dBc/Hz.
{"title":"A 0.49 mm2 CMOS Low-Power TVCO Achieving FoM of 190.36 dBc/Hz for 5G New Radio Application","authors":"P. Shasidharan, S. Mariappan, Li Yizhi, J. Rajendran, Mark Wong","doi":"10.5755/j02.eie.30836","DOIUrl":"https://doi.org/10.5755/j02.eie.30836","url":null,"abstract":"This paper describes the implementation of low-power, low-phase-noise (PN), and robust startup tailless class-C voltage-controlled oscillator (TVCO) for 5G new radio (NR) technology. It features dual gate voltage control source biasing to generate fast startup and differential signal amplitude balancing, thus eliminating the requirement of the conventional tail current source, which introduces more parasitic capacitance that affects the oscillation frequency, phase noise, and power consumption. The TVCO is fabricated in 180 nm complementary metal-oxide semiconductor (CMOS) technology, oscillating at 2.59 GHz 5G NR carrier frequency with an output voltage swing of 1.7 V and low-phase-noise of -122 dBc/Hz at 1 MHz offset with supply voltage headroom of 0.7 V. Without additional features added, the TVCO consumes very low-power and a small die area of 0.98 mW and 0.49 mm2, respectively. The achieved figure of merit (FoM) is 190.36 dBc/Hz.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47182214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. R. U. N. Jafri, Muhammad Owais Ali Siddiqui, Faraz Akbar, Abdul Basit, Sheraz Shamim, Saad Ahmed
This paper presents a method for developing a 3D point cloud map of any indoor and outdoor vicinities using an indigenously developed stationary scanning system comprising of a single low cost 2D laser scanner. The data logging of scanner and required inertial measurement units (IMUs) has been carried out using a Robot Operating System (ROS). Multiple divergent environments have been scanned and 3D point clouds have been developed, which have been found accurate when compared to the ground truth. In addition, the Building Information Model (BIM) of the surveyed vicinities have been developed using generated point clouds. Compared to available surveying solutions present in the local market, the developed system has been found accurate, faster, economical, and user-friendly to generate structural results of the surveyed vicinities in detail.
{"title":"Development of a Low-Cost Stationary Laser Scanning System for Generation of Building Information Models","authors":"S. R. U. N. Jafri, Muhammad Owais Ali Siddiqui, Faraz Akbar, Abdul Basit, Sheraz Shamim, Saad Ahmed","doi":"10.5755/j02.eie.31374","DOIUrl":"https://doi.org/10.5755/j02.eie.31374","url":null,"abstract":"This paper presents a method for developing a 3D point cloud map of any indoor and outdoor vicinities using an indigenously developed stationary scanning system comprising of a single low cost 2D laser scanner. The data logging of scanner and required inertial measurement units (IMUs) has been carried out using a Robot Operating System (ROS). Multiple divergent environments have been scanned and 3D point clouds have been developed, which have been found accurate when compared to the ground truth. In addition, the Building Information Model (BIM) of the surveyed vicinities have been developed using generated point clouds. Compared to available surveying solutions present in the local market, the developed system has been found accurate, faster, economical, and user-friendly to generate structural results of the surveyed vicinities in detail.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46203993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Polyphase filter banks (PFBs) are the most preferred multirate structures for subband coding in Digital Signal Processing (DSP) and communication. For PFB design, there are many important design parameters such as filter length and frequency selectivity. Also, to realize the desired frequency response in designs, stopband and passband attenuation are of considerable importance. In PFB design, researchers and practitioners frequently use iterative and meta-heuristic optimization methods. Heuristic techniques have a significant problem-solving ability in continuous and discrete solution space. Therefore, they give better results than other suggested methods, and their performance depends on the control parameters. In this study, Artificial Bee Colony (ABC) algorithm was employed for suggested design problem of PFB. In the first stage, the control parameters of the ABC algorithm were examined to improve the performance of the proposed PFB problem. In the second stage, the analysis was carried out by changing filter lengths (8-256) and filter band frequencies (0.3-0.7/0.4-0.6). All results obtained were also compared with the Particle Swarm Optimization algorithm (PSO) and the Genetic algorithm (GA). Finally, a DSP application of PFB was carried out according to best results achieved by the ABC algorithm for filter lengths and frequencies.
{"title":"A Novel Approach for Polyphase Filter Bank Design Using ABC Algorithm","authors":"Ahmet Logoglu, S. Kockanat, N. Karaboga","doi":"10.5755/j02.eie.31234","DOIUrl":"https://doi.org/10.5755/j02.eie.31234","url":null,"abstract":"Polyphase filter banks (PFBs) are the most preferred multirate structures for subband coding in Digital Signal Processing (DSP) and communication. For PFB design, there are many important design parameters such as filter length and frequency selectivity. Also, to realize the desired frequency response in designs, stopband and passband attenuation are of considerable importance. In PFB design, researchers and practitioners frequently use iterative and meta-heuristic optimization methods. Heuristic techniques have a significant problem-solving ability in continuous and discrete solution space. Therefore, they give better results than other suggested methods, and their performance depends on the control parameters. In this study, Artificial Bee Colony (ABC) algorithm was employed for suggested design problem of PFB. In the first stage, the control parameters of the ABC algorithm were examined to improve the performance of the proposed PFB problem. In the second stage, the analysis was carried out by changing filter lengths (8-256) and filter band frequencies (0.3-0.7/0.4-0.6). All results obtained were also compared with the Particle Swarm Optimization algorithm (PSO) and the Genetic algorithm (GA). Finally, a DSP application of PFB was carried out according to best results achieved by the ABC algorithm for filter lengths and frequencies.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45570490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blind Source Separation is an optimization method frequently used in statistical signal processing applications. There are many application areas such as ambient listening, denoising, signal detection, and so on. In this study, a new Strength Pareto Evolutionary Algorithm 2-based signal separation method is proposed, which combines Multi-Objective Optimization and Blind Source Separation algorithms. The proposed method has been tested for denoising, which is widely used in biomedical signal processing. That is, the Electrocardiogram (ECG) and White Gaussian Noise are mixed together with normally distributed random numbers and the original signals of the mixed signals are obtained again. To evaluate the performance of the proposed method and others (Multi-Objective Blind Source Separation and Independent Component Analysis), the Signal-to-Noise Ratio (SNR) of the ECG signal obtained from mixed signals has been measured. As a result of the simulation studies, it is seen that the performance of the proposed method is satisfactory.
{"title":"Blind Source Separation with Multi-Objective Optimization for Denoising","authors":"Husamettin Celik, N. Karaboga","doi":"10.5755/j02.eie.31232","DOIUrl":"https://doi.org/10.5755/j02.eie.31232","url":null,"abstract":"Blind Source Separation is an optimization method frequently used in statistical signal processing applications. There are many application areas such as ambient listening, denoising, signal detection, and so on. In this study, a new Strength Pareto Evolutionary Algorithm 2-based signal separation method is proposed, which combines Multi-Objective Optimization and Blind Source Separation algorithms. The proposed method has been tested for denoising, which is widely used in biomedical signal processing. That is, the Electrocardiogram (ECG) and White Gaussian Noise are mixed together with normally distributed random numbers and the original signals of the mixed signals are obtained again. To evaluate the performance of the proposed method and others (Multi-Objective Blind Source Separation and Independent Component Analysis), the Signal-to-Noise Ratio (SNR) of the ECG signal obtained from mixed signals has been measured. As a result of the simulation studies, it is seen that the performance of the proposed method is satisfactory.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45198852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electric load forecasting has been identified as an effective strategy to increase output and revenues in electrical manufacturing and distribution organizations. Several strategies for forecasting power consumption have been suggested; however, they all fail to account for small variations in power demand throughout the prediction. Therefore, the aim of this study was to develop a CRF-based power consumption prediction technique (CRF-PCP) to meet the difficulty of estimating energy consumption (EC). The EC of regions in the area is forecasted using convolution neural networks (CNNs) and conditional random fields (CRFs). Then, using the cloud, the predicted results are delivered to the electricity distribution system. To our knowledge, this is the first attempt to forecast electricity demand using CNN and CRF algorithms. In comparison to state-of-the-art algorithms, this proposed technique achieves 98.9 % accuracy. This recommended work also obtained minimum values of root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean bias error (MBE) by using 10-fold cross-validation (CV) and a hold-out (CV) methodology.
{"title":"Forecasting Energy Demand Using Conditional Random Field and Convolution Neural Network","authors":"Aravind Thangavel, V. Govindaraj","doi":"10.5755/j02.eie.30740","DOIUrl":"https://doi.org/10.5755/j02.eie.30740","url":null,"abstract":"Electric load forecasting has been identified as an effective strategy to increase output and revenues in electrical manufacturing and distribution organizations. Several strategies for forecasting power consumption have been suggested; however, they all fail to account for small variations in power demand throughout the prediction. Therefore, the aim of this study was to develop a CRF-based power consumption prediction technique (CRF-PCP) to meet the difficulty of estimating energy consumption (EC). The EC of regions in the area is forecasted using convolution neural networks (CNNs) and conditional random fields (CRFs). Then, using the cloud, the predicted results are delivered to the electricity distribution system. To our knowledge, this is the first attempt to forecast electricity demand using CNN and CRF algorithms. In comparison to state-of-the-art algorithms, this proposed technique achieves 98.9 % accuracy. This recommended work also obtained minimum values of root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean bias error (MBE) by using 10-fold cross-validation (CV) and a hold-out (CV) methodology.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43778353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yehong Liu, Dong Sun, Baoyan Xu, Shumao Wang, Xin Wang
As the main harvesting machinery, the combine harvester is often due to improper adjustment of its operating parameters resulting in increased crushing rate and grain waste during the harvesting process. To quickly obtain the working range of key operating parameters under low crushing rate, this study conducted field tests on the relevant parameters affecting the crushing rate and finally selected the travel speed, feed rate, threshing drum speed, concave clearance, and crushing rate as node variables for the construction of the Bayesian network model. Based on the “search-and-score” algorithm, the best network structure can be obtained using the combination of the Akaike Information Criterion (AIC) scoring function and the hill-climbing method. In the obtained network, adjusting the proportion of the lowest level of the crushing rate nodes to 100 %, the operation strategy under the condition of low broken rate obtained by the network reasoning was: feed rate < 6 kg/s, travel speed < 5 km/h, concave clearance = 10 mm, threshing drum speed < 900 rpm. Three field trials were carried out using this optimized operation strategy, and the measured crushing rates were 0.93 %, 0.95 %, and 1.07 %, respectively, and the average crushing rate was 0.98 %. At the same time, when the optimized strategy was not used, the crushing rates were, respectively, 1.12 %, 1.41 %, and 1.93 %, and the average crushing rate was 1.48 %. The test results prove that the operation strategy based on Bayesian network inference can effectively reduce the crushing rate in the harvesting process.
{"title":"Combine Harvester Low Crushing Rate Operation Strategy Research by Using Bayesian Network","authors":"Yehong Liu, Dong Sun, Baoyan Xu, Shumao Wang, Xin Wang","doi":"10.5755/j02.eie.31179","DOIUrl":"https://doi.org/10.5755/j02.eie.31179","url":null,"abstract":"As the main harvesting machinery, the combine harvester is often due to improper adjustment of its operating parameters resulting in increased crushing rate and grain waste during the harvesting process. To quickly obtain the working range of key operating parameters under low crushing rate, this study conducted field tests on the relevant parameters affecting the crushing rate and finally selected the travel speed, feed rate, threshing drum speed, concave clearance, and crushing rate as node variables for the construction of the Bayesian network model. Based on the “search-and-score” algorithm, the best network structure can be obtained using the combination of the Akaike Information Criterion (AIC) scoring function and the hill-climbing method. In the obtained network, adjusting the proportion of the lowest level of the crushing rate nodes to 100 %, the operation strategy under the condition of low broken rate obtained by the network reasoning was: feed rate < 6 kg/s, travel speed < 5 km/h, concave clearance = 10 mm, threshing drum speed < 900 rpm. Three field trials were carried out using this optimized operation strategy, and the measured crushing rates were 0.93 %, 0.95 %, and 1.07 %, respectively, and the average crushing rate was 0.98 %. At the same time, when the optimized strategy was not used, the crushing rates were, respectively, 1.12 %, 1.41 %, and 1.93 %, and the average crushing rate was 1.48 %. The test results prove that the operation strategy based on Bayesian network inference can effectively reduce the crushing rate in the harvesting process.\u0000","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42872271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mehmet Korkmaz, Emre Kocyigit, O. K. Sahingoz, B. Diri
Phishing attacks are one of the most preferred types of attacks for cybercriminals, who can easily contact a large number of victims through the use of social networks, particularly through email messages. To protect end users, most of the security mechanisms control Uniform Resource Locator (URL) addresses because of their simplicity of implementation and execution speed. However, due to sophisticated attackers, this mechanism can miss some phishing attacks and has a relatively high false positive rate. In this research, a hybrid technique is proposed that uses not only URL features, but also content-based features as the second level of detection mechanism, thus improving the accuracy of the detection system while also minimizing the number of false positives. Additionally, most phishing detection algorithms use datasets that contain easily differentiated data pieces, either phishing or legitimate. However, in order to implement a more secure protection mechanism, we aimed to collect a larger and high-risk dataset. The proposed approaches were tested on this High-Risk URL and Content-Based Phishing Detection Dataset that only contains suspicious websites from PhishTank. According to experimental studies, an accuracy rate of 98.37 percent was achieved on a more realistic dataset for phishing detection.
{"title":"A Hybrid Phishing Detection System Using Deep Learning-based URL and Content Analysis","authors":"Mehmet Korkmaz, Emre Kocyigit, O. K. Sahingoz, B. Diri","doi":"10.5755/j02.eie.31197","DOIUrl":"https://doi.org/10.5755/j02.eie.31197","url":null,"abstract":"Phishing attacks are one of the most preferred types of attacks for cybercriminals, who can easily contact a large number of victims through the use of social networks, particularly through email messages. To protect end users, most of the security mechanisms control Uniform Resource Locator (URL) addresses because of their simplicity of implementation and execution speed. However, due to sophisticated attackers, this mechanism can miss some phishing attacks and has a relatively high false positive rate. In this research, a hybrid technique is proposed that uses not only URL features, but also content-based features as the second level of detection mechanism, thus improving the accuracy of the detection system while also minimizing the number of false positives. Additionally, most phishing detection algorithms use datasets that contain easily differentiated data pieces, either phishing or legitimate. However, in order to implement a more secure protection mechanism, we aimed to collect a larger and high-risk dataset. The proposed approaches were tested on this High-Risk URL and Content-Based Phishing Detection Dataset that only contains suspicious websites from PhishTank. According to experimental studies, an accuracy rate of 98.37 percent was achieved on a more realistic dataset for phishing detection.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47428831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Process mining is a new field of work that aims to meet the need of the business world to improve efficiency and productivity. This field focuses on analysing, discovering, managing, and improving business processes. Process mining uses event logs as a resource and works on this resource. Hence, the system is developed by analysing the event logs, including each step in the process model. Our study is made up of two significant stages: a data generator for processes and algorithms applied for discovering the created processes. In the first stage, the aim was to develop a simulator with the ability to generate data that could help process modelling and development. Within the framework of this study, a system was created that could work with various process models and extract meaningful information from these models. More productive and efficient processes can be developed as a result of his system. The simulator consists of three modules. The first module is the part where users create a process model. In this module, the user can create his own business process model in the system’s interface or select from other registered models. In the second module, team-based data are simulated through these process models. These generated data are used in the third module, called “analysis”, and meaningful information is extracted. In conclusion, the process can be improved considering the information about time, resource, and cost in the generated data. At the second stage, processes were discovered using alpha, heuristic, and genetic algorithms, which are process mining discovery algorithms and synthetic and real event logs. The discovered processes were demonstrated with Petri nets, and the algorithms’ performances were compared using the fitness function, accuracy rates, and running times. In our study, the heuristic algorithm is more successful because it improves the noise in the data and incomplete processes, which are the disadvantages of the alpha algorithm. However, the genetic algorithm yielded more successful results than the alpha and heuristic algorithms due to its genetic operators.
{"title":"Creating a Data Generator and Implementing Algorithms in Process Analysis","authors":"Çigdem Bakir, Mecit Yuzkat, Fatih Karabiber","doi":"10.5755/j02.eie.31126","DOIUrl":"https://doi.org/10.5755/j02.eie.31126","url":null,"abstract":"Process mining is a new field of work that aims to meet the need of the business world to improve efficiency and productivity. This field focuses on analysing, discovering, managing, and improving business processes. Process mining uses event logs as a resource and works on this resource. Hence, the system is developed by analysing the event logs, including each step in the process model. Our study is made up of two significant stages: a data generator for processes and algorithms applied for discovering the created processes. In the first stage, the aim was to develop a simulator with the ability to generate data that could help process modelling and development. Within the framework of this study, a system was created that could work with various process models and extract meaningful information from these models. More productive and efficient processes can be developed as a result of his system. The simulator consists of three modules. The first module is the part where users create a process model. In this module, the user can create his own business process model in the system’s interface or select from other registered models. In the second module, team-based data are simulated through these process models. These generated data are used in the third module, called “analysis”, and meaningful information is extracted. In conclusion, the process can be improved considering the information about time, resource, and cost in the generated data. At the second stage, processes were discovered using alpha, heuristic, and genetic algorithms, which are process mining discovery algorithms and synthetic and real event logs. The discovered processes were demonstrated with Petri nets, and the algorithms’ performances were compared using the fitness function, accuracy rates, and running times. In our study, the heuristic algorithm is more successful because it improves the noise in the data and incomplete processes, which are the disadvantages of the alpha algorithm. However, the genetic algorithm yielded more successful results than the alpha and heuristic algorithms due to its genetic operators.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47677220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
O. Dziubenko, S. Arhun, A. Hnatov, Dmytro Bogdan, A. Patlins
In connection with the COVID-19 pandemic, there is an urgent need for disinfecting devices that can be used both indoors and in transport. Currently, the most common of these devices are ultraviolet (UV) germicidal lamps. However, they have significant disadvantages, such as short service life, presence of mercury, lack of flexible control, large dimensions, etc. The paper analyzes the sources of UV radiation to find an alternative to UV lamps. Although these elements currently have low efficiency and high cost, etc., it is proposed to use UVC LEDs as a UV source. Due to the COVID-19 pandemic and the general interest in the fight against viruses, as well as the ban on the use of mercury, investments have been attracted in the development of UVC LEDs, which will make them competitive in the future compared to germicidal lamps both in cost and efficiency. The paper presents a disinfection device developed on the basis of UVC LEDs. The principle of operation is described; the control system, the drawing, and the design of the UVC LED-based disinfection device are presented. Due to the described limitations of UVC LEDs, this design can be used for disinfection of small surface areas where frequent on/off switching is required and high power is not required.
{"title":"Device for Inactivation of SARS-CoV-2 Using UVC LEDs","authors":"O. Dziubenko, S. Arhun, A. Hnatov, Dmytro Bogdan, A. Patlins","doi":"10.5755/j02.eie.31140","DOIUrl":"https://doi.org/10.5755/j02.eie.31140","url":null,"abstract":"In connection with the COVID-19 pandemic, there is an urgent need for disinfecting devices that can be used both indoors and in transport. Currently, the most common of these devices are ultraviolet (UV) germicidal lamps. However, they have significant disadvantages, such as short service life, presence of mercury, lack of flexible control, large dimensions, etc. The paper analyzes the sources of UV radiation to find an alternative to UV lamps. Although these elements currently have low efficiency and high cost, etc., it is proposed to use UVC LEDs as a UV source. Due to the COVID-19 pandemic and the general interest in the fight against viruses, as well as the ban on the use of mercury, investments have been attracted in the development of UVC LEDs, which will make them competitive in the future compared to germicidal lamps both in cost and efficiency. The paper presents a disinfection device developed on the basis of UVC LEDs. The principle of operation is described; the control system, the drawing, and the design of the UVC LED-based disinfection device are presented. Due to the described limitations of UVC LEDs, this design can be used for disinfection of small surface areas where frequent on/off switching is required and high power is not required.","PeriodicalId":51031,"journal":{"name":"Elektronika Ir Elektrotechnika","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45941478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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