Pub Date : 2022-12-15DOI: 10.23939/sisn2022.12.199
R. Peleshchak, V. Lytvyn, Mykola Doroshenko, I. Peleshchak, Sviatoslav Sidletskyi
This paper solves two problems: the first problem is devoted to the recognition of distorted symbolic images by a single-layer incompatible dipole neural network, and the second - the optimization of computing resources in the recognition of distorted symbolic images. In particular, the architecture of an incompatible single-layer network with dipole neurons is proposed. Incompatibility of synaptic connections between neurons is based on the fact that significant interaction between dipole neurons exists in their immediate environment. Synaptic connections between dipole neurons are taken into account only between the nearest neighboring neurons, because the synaptic tensor λij between the i -th and j -th dipole neurons is inversely proportional to the distance rij between neighboring i -th and j -th dipole neurons, therefore λij+1<<λij . An algorithm for recognizing incoming distorted symbolic images using an incompatible dipole neural network has been developed and implemented in the Matlab application system. It is shown that for the recognition of input symbol images by an incompatible dipole neural network the computational resource time is shorter compared to a fully connected neural network by n(n+1)/4 times ( n is the number of pixels in columns and rows, respectively, used for encoding of input images). Numerical experiments have shown that the computational time to recognize 0,4n2 distorted characters, which is described by a 5×5 matrix, is 7,5 times less than the recognition time of a fully connected neural network.
{"title":"Distorted character recognition by an incompatible single-layer dipole neural network","authors":"R. Peleshchak, V. Lytvyn, Mykola Doroshenko, I. Peleshchak, Sviatoslav Sidletskyi","doi":"10.23939/sisn2022.12.199","DOIUrl":"https://doi.org/10.23939/sisn2022.12.199","url":null,"abstract":"This paper solves two problems: the first problem is devoted to the recognition of distorted symbolic images by a single-layer incompatible dipole neural network, and the second - the optimization of computing resources in the recognition of distorted symbolic images. In particular, the architecture of an incompatible single-layer network with dipole neurons is proposed. Incompatibility of synaptic connections between neurons is based on the fact that significant interaction between dipole neurons exists in their immediate environment. Synaptic connections between dipole neurons are taken into account only between the nearest neighboring neurons, because the synaptic tensor λij between the i -th and j -th dipole neurons is inversely proportional to the distance rij between neighboring i -th and j -th dipole neurons, therefore λij+1<<λij . An algorithm for recognizing incoming distorted symbolic images using an incompatible dipole neural network has been developed and implemented in the Matlab application system. It is shown that for the recognition of input symbol images by an incompatible dipole neural network the computational resource time is shorter compared to a fully connected neural network by n(n+1)/4 times ( n is the number of pixels in columns and rows, respectively, used for encoding of input images). Numerical experiments have shown that the computational time to recognize 0,4n2 distorted characters, which is described by a 5×5 matrix, is 7,5 times less than the recognition time of a fully connected neural network.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122379380","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 : 2022-12-15DOI: 10.23939/sisn2022.12.023
Yurii Tyshchuk, V. Vysotska, Olha Vlasenko
Speech recognition involves various models, methods and algorithms for analysing and processing the user’s recorded voice. This allows people to control different systems that support one type of speech recognition. A speech-to-text conversion system is a type of speech recognition that uses spoken data for further processing. It also provides several stages for processing an audio file, which uses electroacoustic means, filtering algorithms in the audio file to isolate relevant sounds, electronic data arrays for the selected language, as well as mathematical models that make up the most likely words from phonemes. Thanks to the conversion of speech to text, people whose professions are closely related to typing a large amount of text on the keyboard, significantly speed up and facilitate the work process, as well as reduce the amount of stress. In addition, such systems help businesses, because the concept of remote work is becoming more and more popular, and therefore companies need tools to record and systematize meetings in the form of written text. The object of the research is the process of converting the Ukrainian-language text into a written one based on NLP and machine learning methods. The subject of the research is file processing algorithms for extracting relevant sounds and recognizing phonemes, as well as mathematical models for recognizing an array of phonemes as specific words. The purpose of the work is to design and develop an information system for converting audio Ukrainian-language text into written text based on the Ukrainian Speech-to-text Web application, which is a technology for accurate and easy analysis of Ukrainian-language audio files and their subsequent transcription into text. The application supports downloading files from the file system and recording using the microphone, as well as saving the analysed data. The article also describes the stages of design and the general typical architecture of the corresponding system for converting audio Ukrainian-language text into written text. According to the results of the experimental testing of the developed system, it was found that the number of words does not affect the accuracy of the conversion algorithm, and the decrease in percentage is not large and occurred due to the complexity of the words and the low quality of the microphone, and therefore the recorded file.
{"title":"Information system for converting audio in Ukrainian language into its textual representation using nlp methods and machine learning","authors":"Yurii Tyshchuk, V. Vysotska, Olha Vlasenko","doi":"10.23939/sisn2022.12.023","DOIUrl":"https://doi.org/10.23939/sisn2022.12.023","url":null,"abstract":"Speech recognition involves various models, methods and algorithms for analysing and processing the user’s recorded voice. This allows people to control different systems that support one type of speech recognition. A speech-to-text conversion system is a type of speech recognition that uses spoken data for further processing. It also provides several stages for processing an audio file, which uses electroacoustic means, filtering algorithms in the audio file to isolate relevant sounds, electronic data arrays for the selected language, as well as mathematical models that make up the most likely words from phonemes. Thanks to the conversion of speech to text, people whose professions are closely related to typing a large amount of text on the keyboard, significantly speed up and facilitate the work process, as well as reduce the amount of stress. In addition, such systems help businesses, because the concept of remote work is becoming more and more popular, and therefore companies need tools to record and systematize meetings in the form of written text. The object of the research is the process of converting the Ukrainian-language text into a written one based on NLP and machine learning methods. The subject of the research is file processing algorithms for extracting relevant sounds and recognizing phonemes, as well as mathematical models for recognizing an array of phonemes as specific words. The purpose of the work is to design and develop an information system for converting audio Ukrainian-language text into written text based on the Ukrainian Speech-to-text Web application, which is a technology for accurate and easy analysis of Ukrainian-language audio files and their subsequent transcription into text. The application supports downloading files from the file system and recording using the microphone, as well as saving the analysed data. The article also describes the stages of design and the general typical architecture of the corresponding system for converting audio Ukrainian-language text into written text. According to the results of the experimental testing of the developed system, it was found that the number of words does not affect the accuracy of the conversion algorithm, and the decrease in percentage is not large and occurred due to the complexity of the words and the low quality of the microphone, and therefore the recorded file.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122477653","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 : 2022-12-15DOI: 10.23939/sisn2022.12.219
Oleh Faizulin, Yaroslav Kis
An existing goods accounting information system was assessed for possible infrastructure optimization. A various parts of the system were analyzed to improve infrastructure costs without having a significant degradation of non-functional requirements. Modeling of the optimized system was performed, and evaluation of the infrastructure costs was made. Several optimization directions were evaluated, analyzed and either recommended or rejected. As the result, the final information system model was designed which allows to achieve significant infrastructure cost savings by applying multiple optimizations.
{"title":"Optimization of the infrastructure of the distributed information system of goods accounting","authors":"Oleh Faizulin, Yaroslav Kis","doi":"10.23939/sisn2022.12.219","DOIUrl":"https://doi.org/10.23939/sisn2022.12.219","url":null,"abstract":"An existing goods accounting information system was assessed for possible infrastructure optimization. A various parts of the system were analyzed to improve infrastructure costs without having a significant degradation of non-functional requirements. Modeling of the optimized system was performed, and evaluation of the infrastructure costs was made. Several optimization directions were evaluated, analyzed and either recommended or rejected. As the result, the final information system model was designed which allows to achieve significant infrastructure cost savings by applying multiple optimizations.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127444026","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 : 2022-12-15DOI: 10.23939/sisn2022.12.052
Oleksiy Kuznietsov, V. Vysotska, Olha Vlasenko
Virtual reality is an important information technology that allows to achieve significant progress in underserved areas. Immersive multimedia, or virtual reality, is a software-simulated environment that simulates physical presence in the real or imagined world. Innovative applications such as high-tech intelligent systems that correlate with the information technologies of display, modelling, building and maintaining networks, artificial touch and computer graphics have made virtual reality a breakthrough in the computing world. Excursions and distance learning in virtual reality are one of the ways to simulate the presence in a city in which a person cannot be physically present at the moment. When viewing virtual tours or attending online classes using videos/photos, the user (applicant/student/learner/teacher) only sees a flat image and cannot interact with it. In this way, the effect that the user is present in that place is lost. Virtual reality with the effect of full immersion allows to eliminate these disadvantages almost completely, and to provide the opportunity to interact with objects located on the virtual stage with the help of real body movements. In addition, in a short period of time, with the help of virtual reality, the user can visit many places, literally without leaving home. This is impossible to do in real life, as certain places are located at a great distance from the user. The object of the study is the process of conducting an interactive excursion and distance learning on the basis of the Department of Information Systems and Networks of the Lviv Polytechnic National University in virtual reality. The subject of the study comprises means, methods of designing and developing the virtual reality information system of excursions and distance learning using virtual reality information technologies. The practical significance of the obtained results is the implemented information system for conducting interactive excursions and distance learning on the basis of the university department. The scientific novelty of the obtained results is an information system based on the use of virtual reality, which is intended for online visits to the premises of the university department with elements of full immersion, as a platform for career guidance of students or distance learning of students.
{"title":"The virtual reality information system for the ISN LPNU department tours with elements of full immersion as a platform for an open day","authors":"Oleksiy Kuznietsov, V. Vysotska, Olha Vlasenko","doi":"10.23939/sisn2022.12.052","DOIUrl":"https://doi.org/10.23939/sisn2022.12.052","url":null,"abstract":"Virtual reality is an important information technology that allows to achieve significant progress in underserved areas. Immersive multimedia, or virtual reality, is a software-simulated environment that simulates physical presence in the real or imagined world. Innovative applications such as high-tech intelligent systems that correlate with the information technologies of display, modelling, building and maintaining networks, artificial touch and computer graphics have made virtual reality a breakthrough in the computing world. Excursions and distance learning in virtual reality are one of the ways to simulate the presence in a city in which a person cannot be physically present at the moment. When viewing virtual tours or attending online classes using videos/photos, the user (applicant/student/learner/teacher) only sees a flat image and cannot interact with it. In this way, the effect that the user is present in that place is lost. Virtual reality with the effect of full immersion allows to eliminate these disadvantages almost completely, and to provide the opportunity to interact with objects located on the virtual stage with the help of real body movements. In addition, in a short period of time, with the help of virtual reality, the user can visit many places, literally without leaving home. This is impossible to do in real life, as certain places are located at a great distance from the user. The object of the study is the process of conducting an interactive excursion and distance learning on the basis of the Department of Information Systems and Networks of the Lviv Polytechnic National University in virtual reality. The subject of the study comprises means, methods of designing and developing the virtual reality information system of excursions and distance learning using virtual reality information technologies. The practical significance of the obtained results is the implemented information system for conducting interactive excursions and distance learning on the basis of the university department. The scientific novelty of the obtained results is an information system based on the use of virtual reality, which is intended for online visits to the premises of the university department with elements of full immersion, as a platform for career guidance of students or distance learning of students.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115620768","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 : 2022-12-15DOI: 10.23939/sisn2022.12.079
Y. Matseliukh, M. Bublyk, V. Vysotska
In order to increase the attractiveness of public transport for urban residents, a software product has been created for transport companies that, by visualizing passenger traffic, helps to improve the quality of public transport services provided within the city. The paper analyses existing and current scientific developments and literature sources, which show the advantages and disadvantages of a large number of different algorithms and methods, approaches, and methods for solving problems of 2D- visualization of passenger flows on public routes. As a result of the research, stable connections have been established between the factors and criteria involved in assessing the quality of passenger transport services. The system analysis of the designed system is executed, and examples of the structure of an intelligent system of 2D visualization of passenger flows are created. The connections of the system with the essential elements of the external world are analysed. For a visual representation, diagrams of usage variants, classes, sequences, states, and activities are created according to UML notation. Our own unique algorithms have been created for displaying visualizations in two different modes: schematic and “on the map”. In the “on the map” mode, a method of calculating data on the movement of transport units on the route was successfully applied for 2D visualization on the screen, taking into account the absolute values of geographical coordinates in the world. This avoids unnecessary errors and inaccuracies in the calculations. An artificial neural network has been developed that operates using the RMSprop learning algorithm. The artificial neural network predicts how the values of passenger traffic will change when adjusting the schedule of the transport unit on the route. The obtained results make it possible to form and substantiate the expediency of changing the schedule of the vehicle running on the route in order to make more efficient use of races during peak times.
{"title":"Intelligent system of passenger flows dynamic 2D-visualization for public transport routes","authors":"Y. Matseliukh, M. Bublyk, V. Vysotska","doi":"10.23939/sisn2022.12.079","DOIUrl":"https://doi.org/10.23939/sisn2022.12.079","url":null,"abstract":"In order to increase the attractiveness of public transport for urban residents, a software product has been created for transport companies that, by visualizing passenger traffic, helps to improve the quality of public transport services provided within the city. The paper analyses existing and current scientific developments and literature sources, which show the advantages and disadvantages of a large number of different algorithms and methods, approaches, and methods for solving problems of 2D- visualization of passenger flows on public routes. As a result of the research, stable connections have been established between the factors and criteria involved in assessing the quality of passenger transport services. The system analysis of the designed system is executed, and examples of the structure of an intelligent system of 2D visualization of passenger flows are created. The connections of the system with the essential elements of the external world are analysed. For a visual representation, diagrams of usage variants, classes, sequences, states, and activities are created according to UML notation. Our own unique algorithms have been created for displaying visualizations in two different modes: schematic and “on the map”. In the “on the map” mode, a method of calculating data on the movement of transport units on the route was successfully applied for 2D visualization on the screen, taking into account the absolute values of geographical coordinates in the world. This avoids unnecessary errors and inaccuracies in the calculations. An artificial neural network has been developed that operates using the RMSprop learning algorithm. The artificial neural network predicts how the values of passenger traffic will change when adjusting the schedule of the transport unit on the route. The obtained results make it possible to form and substantiate the expediency of changing the schedule of the vehicle running on the route in order to make more efficient use of races during peak times.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134633044","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 : 2022-12-15DOI: 10.23939/sisn2022.12.141
Petro Zdebskyi, A. Berko, L. Chyrun
The purpose of the work is to develop a project of an information and reference system for finding answers to questions based on the highest degree of comparison using text content from open English- language web resources. Examples of such questions can be: “What is the best book ever?”, “What is the most popular IDE for Python”. The result of the functioning of the information and reference system is a ranked list of answers based on the frequency of appearance of each of the answer options. Also, a numerical characteristic of the probability of the preference of a particular answer over others is added to each element of the list. Based on this metric, the obtained results are ranked. This information and reference system works with questions to which there is no unequivocal answer, what differs it from classic information systems for finding answers to questions of the QA-system type. The latter have a hypothesis that there is only one true answer to the question, often such systems work with well-known facts. Examples of questions they answer can be, for example, the date of birth of a famous person, or the population of a certain country. Instead, the proposed information and reference system answers subjective questions, for example, “What is the best book in the fantasy genre?” or “What is the best programming language?”. The system is based on the popularity of one or another answer. Proper names based on the analysis of N-grams are also keywords for forming the answer to the question.
{"title":"Information system for extraction of information from open web resources","authors":"Petro Zdebskyi, A. Berko, L. Chyrun","doi":"10.23939/sisn2022.12.141","DOIUrl":"https://doi.org/10.23939/sisn2022.12.141","url":null,"abstract":"The purpose of the work is to develop a project of an information and reference system for finding answers to questions based on the highest degree of comparison using text content from open English- language web resources. Examples of such questions can be: “What is the best book ever?”, “What is the most popular IDE for Python”. The result of the functioning of the information and reference system is a ranked list of answers based on the frequency of appearance of each of the answer options. Also, a numerical characteristic of the probability of the preference of a particular answer over others is added to each element of the list. Based on this metric, the obtained results are ranked. This information and reference system works with questions to which there is no unequivocal answer, what differs it from classic information systems for finding answers to questions of the QA-system type. The latter have a hypothesis that there is only one true answer to the question, often such systems work with well-known facts. Examples of questions they answer can be, for example, the date of birth of a famous person, or the population of a certain country. Instead, the proposed information and reference system answers subjective questions, for example, “What is the best book in the fantasy genre?” or “What is the best programming language?”. The system is based on the popularity of one or another answer. Proper names based on the analysis of N-grams are also keywords for forming the answer to the question.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"41 36","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133390319","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 : 2022-06-15DOI: 10.23939/sisn2022.11.127
O. Veres, Yana Levus
The work is devoted to research on the problem of management and organization of free time during the period of forced stay at home by means of information technologies. The paper describes the problems during quarantine restrictions and how this affects the psycho- emotional health of the person. The need to adapt and modify the usual forms of leisure activity to the new format has been determined. The most famous modern information systems, providing entertainment services are narrow-purpose systems. They generate recommendations related to media services. Methods of providing recommendations have been studied. A tree of goals was built to solve the problem situation. Alternative means of implementation of the information system are considered. Using the method of the hierarchical analysis, the optimal system type of implementation of the proposed solution is chosen – the recommendation system. The algorithm of work of the recommendation system of free time during the period of forced stay at home is described. The mechanism of weight optimization in the weighted hybrid recommendation algorithm was used to provide recommendations. When a user's portrait is created, the method of the personality type indicator is used. Using the UML language tools, a conceptual system model has been designed. For realization of the prototype of a mobile application of the system language programming Java, JavaScript, frame react Native is chosen. To work with the database the MySQL database management system has been selected. An example of using the system as a mobile application is given. The main stages of interaction of the user with the recommended system of free time during the period of forced stay at home are described. The work of the recommendation system is aimed at mitigating the negative consequences on the psycho-emotional state of a person who is in the conditions of forced quarantine. The special feature of the recommendations of the developed prototype is to offer, in addition to passive activities, active actions that take into account the peculiarities of each user. Application of the system is not limited only to quarantine. The services of the system will be appropriate for people with disabilities, in the case of physical injury transfer or liquidation, which led to temporary immobility.
{"title":"Recommendation System for Planning Leisure in Quarantine Conditions","authors":"O. Veres, Yana Levus","doi":"10.23939/sisn2022.11.127","DOIUrl":"https://doi.org/10.23939/sisn2022.11.127","url":null,"abstract":"The work is devoted to research on the problem of management and organization of free time during the period of forced stay at home by means of information technologies. The paper describes the problems during quarantine restrictions and how this affects the psycho- emotional health of the person. The need to adapt and modify the usual forms of leisure activity to the new format has been determined. The most famous modern information systems, providing entertainment services are narrow-purpose systems. They generate recommendations related to media services. Methods of providing recommendations have been studied. A tree of goals was built to solve the problem situation. Alternative means of implementation of the information system are considered. Using the method of the hierarchical analysis, the optimal system type of implementation of the proposed solution is chosen – the recommendation system. The algorithm of work of the recommendation system of free time during the period of forced stay at home is described. The mechanism of weight optimization in the weighted hybrid recommendation algorithm was used to provide recommendations. When a user's portrait is created, the method of the personality type indicator is used. Using the UML language tools, a conceptual system model has been designed. For realization of the prototype of a mobile application of the system language programming Java, JavaScript, frame react Native is chosen. To work with the database the MySQL database management system has been selected. An example of using the system as a mobile application is given. The main stages of interaction of the user with the recommended system of free time during the period of forced stay at home are described. The work of the recommendation system is aimed at mitigating the negative consequences on the psycho-emotional state of a person who is in the conditions of forced quarantine. The special feature of the recommendations of the developed prototype is to offer, in addition to passive activities, active actions that take into account the peculiarities of each user. Application of the system is not limited only to quarantine. The services of the system will be appropriate for people with disabilities, in the case of physical injury transfer or liquidation, which led to temporary immobility.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124685197","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 : 2022-06-15DOI: 10.23939/sisn2022.11.013
Sofiia Tatchyn, T. Basyuk
The authors of the article have developed methodological grounds, designed and constructed an information system to implement protected voting. The analysis of the main ways of using information technology in voting area has resulted in the finding that mobile devices with certain software can significantly reduce the number of visits to polling stations, which make political voting much more accessible to people. The authors have designed the information system using a structural approach and design model Data Flow Diagrams (DFD). They have also developed a context diagram of the information system and decomposed its main process to demonstrate ways to convert input into output. Algorithm of work have been presented in the form of a Petri net, also the authors have specified on the tables of positions and transitions of this network for a better understanding of system features. The functional purpose has been presented, the analysis of software tools has been done that allows us to achieve the set goals in designing the system. Verification of work has been carried out which is proved in screenshots of program windows of the system and contents of the main pages has also been described.
{"title":"Information System for Supporting the Process of Protected Voting","authors":"Sofiia Tatchyn, T. Basyuk","doi":"10.23939/sisn2022.11.013","DOIUrl":"https://doi.org/10.23939/sisn2022.11.013","url":null,"abstract":"The authors of the article have developed methodological grounds, designed and constructed an information system to implement protected voting. The analysis of the main ways of using information technology in voting area has resulted in the finding that mobile devices with certain software can significantly reduce the number of visits to polling stations, which make political voting much more accessible to people. The authors have designed the information system using a structural approach and design model Data Flow Diagrams (DFD). They have also developed a context diagram of the information system and decomposed its main process to demonstrate ways to convert input into output. Algorithm of work have been presented in the form of a Petri net, also the authors have specified on the tables of positions and transitions of this network for a better understanding of system features. The functional purpose has been presented, the analysis of software tools has been done that allows us to achieve the set goals in designing the system. Verification of work has been carried out which is proved in screenshots of program windows of the system and contents of the main pages has also been described.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126784125","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 : 2022-06-15DOI: 10.23939/sisn2022.11.103
Mykola Baranov, Y. Shcherbyna
Image classification task is a very important problem of a computer vision area. The first approaches to image classification tasks belong to a classic straightforward algorithm. Despite the successful applications of such algorithms a lot of image classification tasks had not been solved until machine learning approaches were involved in a computer vision area. An early successful result of machine learning applications helps researchers with extracted features classification which was not available without machine learning models. But handcrafter features were required which left the most complicated classification task impossible to solve. Recent success in deep learning allows researchers to implement automatic trainable feature extraction. This gave significant progress in the computer vision area last but not least. Processing large-scale datasets bring researchers great progress in automatic feature extraction thus combining such features with precious approaches led to groundbreaking in computer vision. But a new limitation has come - dependency on large amounts of data. Deep learning approaches to image classification task usually requires large-scale datasets. Moreover, modern models lead to unexpected behavior in distribution datasets. A few-shot learning approach of deep learning models allows us to dramatically reduce the amount of required data while keeping the same promising results. Despite reduced datasets, there is still a tradeoff between the amount of available data and trained model performance. In this paper, we implemented a siamese network based on triplet loss. Then, we investigate a relationship between the amount of available data and few-shot model performances. We compare the models obtained by metric-learning with baselines models trained using large-scale datasets.
{"title":"Comprehensive Analysis of Few-shot Image Classification Method Using Triplet Loss","authors":"Mykola Baranov, Y. Shcherbyna","doi":"10.23939/sisn2022.11.103","DOIUrl":"https://doi.org/10.23939/sisn2022.11.103","url":null,"abstract":"Image classification task is a very important problem of a computer vision area. The first approaches to image classification tasks belong to a classic straightforward algorithm. Despite the successful applications of such algorithms a lot of image classification tasks had not been solved until machine learning approaches were involved in a computer vision area. An early successful result of machine learning applications helps researchers with extracted features classification which was not available without machine learning models. But handcrafter features were required which left the most complicated classification task impossible to solve. Recent success in deep learning allows researchers to implement automatic trainable feature extraction. This gave significant progress in the computer vision area last but not least. Processing large-scale datasets bring researchers great progress in automatic feature extraction thus combining such features with precious approaches led to groundbreaking in computer vision. But a new limitation has come - dependency on large amounts of data. Deep learning approaches to image classification task usually requires large-scale datasets. Moreover, modern models lead to unexpected behavior in distribution datasets. A few-shot learning approach of deep learning models allows us to dramatically reduce the amount of required data while keeping the same promising results. Despite reduced datasets, there is still a tradeoff between the amount of available data and trained model performance. In this paper, we implemented a siamese network based on triplet loss. Then, we investigate a relationship between the amount of available data and few-shot model performances. We compare the models obtained by metric-learning with baselines models trained using large-scale datasets.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121079906","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 : 2022-06-15DOI: 10.23939/sisn2022.11.145
N. Oleksiv, V. Vysotska
It is acknowledged that each person's life, group of people and nation is formed depending on geographical, economic, political, cultural and religious conditions. Lifestyle is formed as a result of daily repetition and consists of the following factors: nutrition, exercise, the presence of bad habits, moral and spiritual development, and so on. In recent decades, lifestyle has been considered an integral part of well-being, leading to increased research. According to the scientist's study, more than half of health problems are related to diet. Millions of people eat incorrectly and are not even aware of it. The actuality of the theme: there are many approaches to solving the problem of diet control, but it should be understood that different analogues offer different opportunities that are not always clear and convenient. It is because there are several ways to achieve the same goal. The need for research on healthy eating in modern conditions is one of the priority tasks to improve the physical condition of different age groups. The aim is to create a system that will be aimed at helping the end-user to follow a healthy diet by determining the composition and caloric content of the product and the formation of recommendations based on the appropriate rhythm of life. The system is designed to solve specific tasks: to recognize products, correlate the product and its caloric content, form a food diary, remind the user about missed meals and keep statistics.
{"title":"Mobile Information System for Human Nutrition Control","authors":"N. Oleksiv, V. Vysotska","doi":"10.23939/sisn2022.11.145","DOIUrl":"https://doi.org/10.23939/sisn2022.11.145","url":null,"abstract":"It is acknowledged that each person's life, group of people and nation is formed depending on geographical, economic, political, cultural and religious conditions. Lifestyle is formed as a result of daily repetition and consists of the following factors: nutrition, exercise, the presence of bad habits, moral and spiritual development, and so on. In recent decades, lifestyle has been considered an integral part of well-being, leading to increased research. According to the scientist's study, more than half of health problems are related to diet. Millions of people eat incorrectly and are not even aware of it. The actuality of the theme: there are many approaches to solving the problem of diet control, but it should be understood that different analogues offer different opportunities that are not always clear and convenient. It is because there are several ways to achieve the same goal. The need for research on healthy eating in modern conditions is one of the priority tasks to improve the physical condition of different age groups. The aim is to create a system that will be aimed at helping the end-user to follow a healthy diet by determining the composition and caloric content of the product and the formation of recommendations based on the appropriate rhythm of life. The system is designed to solve specific tasks: to recognize products, correlate the product and its caloric content, form a food diary, remind the user about missed meals and keep statistics.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130719169","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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