Pub Date : 2023-07-15DOI: 10.23939/sisn2023.13.156
Andrii Vasyluk, T. Basyuk
The distribution of resources is an important scientific and practical task, as it concerns all areas of human activity, the field of information technologies is no exception. A study was conducted, which showed that today there are many approaches to solving the given problem, each of which is characterized by certain features. Known methods of resource allocation are analyzed, their classification is given and it is shown that they are mainly defined as linear programming problems, resource allocation matrices or are implemented on the basis of empirical knowledge. With this in mind, the authors analyzed the mechanisms of the algebra of algorithms, determined their scopes of application, and made a decision regarding their use for modeling the distribution of resources in the field of information technologies. Further work was aimed at building a tree of goals, which made it possible to reflect the general goal and sub-goals that must be ensured in order to effectively allocate resources. An analysis was carried out and development tools were selected. The result of the work was a prototype of the software that implements the modeling of resource distribution using the Balash method and the algorithm algebra apparatus. Further research will be aimed at verifying the operation of the system and designing related modules.
{"title":"Algebras of algorithms for modeling the distribution of resources in IT projects","authors":"Andrii Vasyluk, T. Basyuk","doi":"10.23939/sisn2023.13.156","DOIUrl":"https://doi.org/10.23939/sisn2023.13.156","url":null,"abstract":"The distribution of resources is an important scientific and practical task, as it concerns all areas of human activity, the field of information technologies is no exception. A study was conducted, which showed that today there are many approaches to solving the given problem, each of which is characterized by certain features. Known methods of resource allocation are analyzed, their classification is given and it is shown that they are mainly defined as linear programming problems, resource allocation matrices or are implemented on the basis of empirical knowledge. With this in mind, the authors analyzed the mechanisms of the algebra of algorithms, determined their scopes of application, and made a decision regarding their use for modeling the distribution of resources in the field of information technologies. Further work was aimed at building a tree of goals, which made it possible to reflect the general goal and sub-goals that must be ensured in order to effectively allocate resources. An analysis was carried out and development tools were selected. The result of the work was a prototype of the software that implements the modeling of resource distribution using the Balash method and the algorithm algebra apparatus. Further research will be aimed at verifying the operation of the system and designing related modules.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123291062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-15DOI: 10.23939/sisn2023.13.350
Diana Koshtura
Gender recognition from voice is a challenging problem in speech processing. This task involves extracting meaningful features from speech signals and classifying them into male or female categories. In this article, was implemented a gender recognition system using Python programming. I first recorded voice samples from both male and female speakers and extracted Mel-frequency cepstral coefficients (MFCC) as features. Then trained, a Support VectorMachine (SVM) classifier was on these features and evaluated its performance using accuracy, precision, recall, and F1-score metrics. These experiments demonstrated that proposed system should achieve high accuracy on the test set and will accurately predict the gender of a speaker based on their voice. I also explored using pre-trained models to reduce the need for large amounts of training data and found that they can provide good performance while requiring less computation. This study highlights the potential of using machine learning techniques for gender recognition from voice and can be extended to other speech processing applications.
{"title":"Information technology for gender recognition by voice","authors":"Diana Koshtura","doi":"10.23939/sisn2023.13.350","DOIUrl":"https://doi.org/10.23939/sisn2023.13.350","url":null,"abstract":"Gender recognition from voice is a challenging problem in speech processing. This task involves extracting meaningful features from speech signals and classifying them into male or female categories. In this article, was implemented a gender recognition system using Python programming. I first recorded voice samples from both male and female speakers and extracted Mel-frequency cepstral coefficients (MFCC) as features. Then trained, a Support VectorMachine (SVM) classifier was on these features and evaluated its performance using accuracy, precision, recall, and F1-score metrics. These experiments demonstrated that proposed system should achieve high accuracy on the test set and will accurately predict the gender of a speaker based on their voice. I also explored using pre-trained models to reduce the need for large amounts of training data and found that they can provide good performance while requiring less computation. This study highlights the potential of using machine learning techniques for gender recognition from voice and can be extended to other speech processing applications.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125868194","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/sisn2022.12.255
Taras Voloshko, T. Shestakevych
The game industry works to meet the needs of millions of users, so developers are actively improving existing games and developing a new one. Hyper-casual is a game with a simple plot, simple mechanics, and a primitive user interface. Despite the seeming simplicity, such games are popular and bring significant profits to developers. The life cycle of a hypercasual game can be quite short – a few weeks, or months, which also involves a limited time to develop such a game. It is advisable to have a tool to identify, evaluate and consider the characteristics of successful hyper-casual games. Therefore, the actual task is to develop a structure for describing a hyper-casual game so that, based on such structured data, a decision can be made regarding the relevant characteristics of a successful game. Hyper-casual games in the entertainment industry are one of the genres of games for mobile platforms. To determine the relevant characteristics of such a game, it is necessary to accumulate data on successful games, determine the general characteristics common to all hyper-casual games, to structure the obtained data, and select the characteristics that affect the success of the game. To decide on the relevance of characteristics, it is worth analyzing the structured data describing the game. The selected characteristics will be implemented in the hyper-casual game. The relevant characteristics of the game are a significant criterion for choosing a game engine for game development. According to such criteria, it is worth evaluating popular game engines – GameMaker, Godot, Unreal Engine, and Unity. To decide on the best engine, it is advisable to use the analytic hierarchy method. Facebook Analytics will be used to accumulate data on the success of the developed game. The proposed concept of determining the relevant characteristics of various information technologies will allow combining such technologies into a single system.
{"title":"Identifying relevant characteristics for the development of a hyper-casual game","authors":"Taras Voloshko, T. Shestakevych","doi":"10.23939/sisn2022.12.255","DOIUrl":"https://doi.org/10.23939/sisn2022.12.255","url":null,"abstract":"The game industry works to meet the needs of millions of users, so developers are actively improving existing games and developing a new one. Hyper-casual is a game with a simple plot, simple mechanics, and a primitive user interface. Despite the seeming simplicity, such games are popular and bring significant profits to developers. The life cycle of a hypercasual game can be quite short – a few weeks, or months, which also involves a limited time to develop such a game. It is advisable to have a tool to identify, evaluate and consider the characteristics of successful hyper-casual games. Therefore, the actual task is to develop a structure for describing a hyper-casual game so that, based on such structured data, a decision can be made regarding the relevant characteristics of a successful game. Hyper-casual games in the entertainment industry are one of the genres of games for mobile platforms. To determine the relevant characteristics of such a game, it is necessary to accumulate data on successful games, determine the general characteristics common to all hyper-casual games, to structure the obtained data, and select the characteristics that affect the success of the game. To decide on the relevance of characteristics, it is worth analyzing the structured data describing the game. The selected characteristics will be implemented in the hyper-casual game. The relevant characteristics of the game are a significant criterion for choosing a game engine for game development. According to such criteria, it is worth evaluating popular game engines – GameMaker, Godot, Unreal Engine, and Unity. To decide on the best engine, it is advisable to use the analytic hierarchy method. Facebook Analytics will be used to accumulate data on the success of the developed game. The proposed concept of determining the relevant characteristics of various information technologies will allow combining such technologies into a single system.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"84 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":"114505835","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/sisn2022.12.177
D. Dosyn, Andriy Yatsenko, V. Kovalevych, Y. Daradkeh
The widespread implementation of intelligent decision support systems (IDSS) is hampered by the lack of methods and technologies for automatically filling the knowledge base during the operation of such systems. This problem is especially acute in the medical field. Its solution lies in the application of automatic planning technologies. The methods and algorithms developed in this field for estimation the optimal strategy for solving problems, which are strictly formulated in terms of predicate logic, allow numerically evaluating the usefulness of new messages and thus ranking information by importance and automatically selecting essential information for entering it into the knowledge base. The paper proposes the architecture of a medical IDSS that implements this approach, substantiates the applicability of the Markov approximation for the formalization of automatic planning tasks in the medical field, shows the effectiveness of the proposed approach using the example of an informed choice of serum for influenza vaccination.
{"title":"Application of automated planning technologies for completing the medical knowledge base","authors":"D. Dosyn, Andriy Yatsenko, V. Kovalevych, Y. Daradkeh","doi":"10.23939/sisn2022.12.177","DOIUrl":"https://doi.org/10.23939/sisn2022.12.177","url":null,"abstract":"The widespread implementation of intelligent decision support systems (IDSS) is hampered by the lack of methods and technologies for automatically filling the knowledge base during the operation of such systems. This problem is especially acute in the medical field. Its solution lies in the application of automatic planning technologies. The methods and algorithms developed in this field for estimation the optimal strategy for solving problems, which are strictly formulated in terms of predicate logic, allow numerically evaluating the usefulness of new messages and thus ranking information by importance and automatically selecting essential information for entering it into the knowledge base. The paper proposes the architecture of a medical IDSS that implements this approach, substantiates the applicability of the Markov approximation for the formalization of automatic planning tasks in the medical field, shows the effectiveness of the proposed approach using the example of an informed choice of serum for influenza vaccination.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"14 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":"129758541","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/sisn2022.12.007
Oleksii Neretin, V. Kharchenko
In recent years, many companies have begun to integrate artificial intelligence systems (AIS) into their infrastructures. AIS is used in sensitive areas of society, such as the judicial system, critical infrastructure, video surveillance, and others. This determines the need for a reliable assessment and guaranteed provision of cyber security of AIS. The study analyzed the state of affairs regarding the cyber security of these systems. Possible types of attacks are classified and the main ones are considered in detail. Threats and attacks were analyzed by level of severity and security risks were assessed using the IMECA method. “Adversarial attacks” and “Data poisoning” attacks are found to have the highest risks of danger, but the countermeasures are not at the appropriate level. It was concluded that there is a need for formalization and standardization of the life cycle of the development and use of secure AIS. The directions of further research regarding the need to develop methods for evaluating and ensuring cyber security of the AIS are substantiated, including for systems that provide AI as a service.
{"title":"Ensurance of artificial intelligence systems cyber security: analysis of vulnerabilities, attacks and countermeasures","authors":"Oleksii Neretin, V. Kharchenko","doi":"10.23939/sisn2022.12.007","DOIUrl":"https://doi.org/10.23939/sisn2022.12.007","url":null,"abstract":"In recent years, many companies have begun to integrate artificial intelligence systems (AIS) into their infrastructures. AIS is used in sensitive areas of society, such as the judicial system, critical infrastructure, video surveillance, and others. This determines the need for a reliable assessment and guaranteed provision of cyber security of AIS. The study analyzed the state of affairs regarding the cyber security of these systems. Possible types of attacks are classified and the main ones are considered in detail. Threats and attacks were analyzed by level of severity and security risks were assessed using the IMECA method. “Adversarial attacks” and “Data poisoning” attacks are found to have the highest risks of danger, but the countermeasures are not at the appropriate level. It was concluded that there is a need for formalization and standardization of the life cycle of the development and use of secure AIS. The directions of further research regarding the need to develop methods for evaluating and ensuring cyber security of the AIS are substantiated, including for systems that provide AI as a service.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"11 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":"130763774","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/sisn2022.12.120
Nazar Borovets, I. Rishnyak, L. Chyrun
oday, the issue of tourism, travel, research of the city or its history remains quite relevant. Awareness of one’s identity, learning the history of one’s people are important aspects of life, or learning the culture of other peoples. Although the Covid-19 pandemic and the war have put this issue on the back burner, it adds new challenges to it. On the one hand, interest in research and learning something new is enhanced by isolation, both internal - limiting people’s personal contacts, and external – closed borders and a limited flow of tourists. On the other hand, it creates new requirements for providing and using tourism as a product. But these are only additional time factors. The essence of tourism, travel and research is not going anywhere. The goal of the project: to create a new information system that will help in the formation of the tourism product of small towns.
{"title":"Information system project for startup of supporting internet tourism in Ukrainian territory","authors":"Nazar Borovets, I. Rishnyak, L. Chyrun","doi":"10.23939/sisn2022.12.120","DOIUrl":"https://doi.org/10.23939/sisn2022.12.120","url":null,"abstract":"oday, the issue of tourism, travel, research of the city or its history remains quite relevant. Awareness of one’s identity, learning the history of one’s people are important aspects of life, or learning the culture of other peoples. Although the Covid-19 pandemic and the war have put this issue on the back burner, it adds new challenges to it. On the one hand, interest in research and learning something new is enhanced by isolation, both internal - limiting people’s personal contacts, and external – closed borders and a limited flow of tourists. On the other hand, it creates new requirements for providing and using tourism as a product. But these are only additional time factors. The essence of tourism, travel and research is not going anywhere. The goal of the project: to create a new information system that will help in the formation of the tourism product of small towns.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"29 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":"127086052","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/sisn2022.12.001
Mykola Baranov, Y. Shcherbyna, Oles Khodych
In today’s world, the amount of available information grows exponentially every day. Most of this data is visual data. Correspondingly, the demand for the algorithm of image rent is growing. Traditionally, the first approaches to computer vision problems were classical algorithms without the use of machine learning. Such approaches are limited by many factors. First of all, the conditions imposed on the input images are applied – the shooting angle, lighting, position of objects on the scene, etc. Other classical algorithms cannot meet the needs of modern computer vision problems. Neural network approaches and deep learning models have largely replaced classical programming algorithms. The greatest advantage of deep neural networks in computer vision tasks is not only the possibility of automatically building data processing algorithms that cannot be built in any other way, but also the comprehensiveness of such an approach – actual deep neural networks provide all stages of image processing from start to finish. But. This approach is not always optimal. Training models require a large amount of annotated data to avoid the effect of overfitting such models. In many settings, the conditions have a significant degree of variability, but are limited. In such cases, the combination of both approaches of computer vision is fruitful – pre-processing of the image is performed by classical algorithms, and prediction (classification, object search, etc.) is performed by a neural network. This article noted an example of the use of damaged images in the classification of tasks (in the extreme cases, the percentage of damage reached 60 % of the image area). We have shown in practice that the use of classic approaches for restoration of damaged areas of the image (inpainting) made it possible to increase the final accuracy of the model by up to 10 % compared to the base model trained under identical conditions on the original data.
{"title":"Exploit computer vision inpainting approach to boost deep learning models","authors":"Mykola Baranov, Y. Shcherbyna, Oles Khodych","doi":"10.23939/sisn2022.12.001","DOIUrl":"https://doi.org/10.23939/sisn2022.12.001","url":null,"abstract":"In today’s world, the amount of available information grows exponentially every day. Most of this data is visual data. Correspondingly, the demand for the algorithm of image rent is growing. Traditionally, the first approaches to computer vision problems were classical algorithms without the use of machine learning. Such approaches are limited by many factors. First of all, the conditions imposed on the input images are applied – the shooting angle, lighting, position of objects on the scene, etc. Other classical algorithms cannot meet the needs of modern computer vision problems. Neural network approaches and deep learning models have largely replaced classical programming algorithms. The greatest advantage of deep neural networks in computer vision tasks is not only the possibility of automatically building data processing algorithms that cannot be built in any other way, but also the comprehensiveness of such an approach – actual deep neural networks provide all stages of image processing from start to finish. But. This approach is not always optimal. Training models require a large amount of annotated data to avoid the effect of overfitting such models. In many settings, the conditions have a significant degree of variability, but are limited. In such cases, the combination of both approaches of computer vision is fruitful – pre-processing of the image is performed by classical algorithms, and prediction (classification, object search, etc.) is performed by a neural network. This article noted an example of the use of damaged images in the classification of tasks (in the extreme cases, the percentage of damage reached 60 % of the image area). We have shown in practice that the use of classic approaches for restoration of damaged areas of the image (inpainting) made it possible to increase the final accuracy of the model by up to 10 % compared to the base model trained under identical conditions on the original data.","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":"114239196","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/sisn2022.12.169
Pavlo Pukach
This paper analyzes and compares modern deep learning models for the classification of MRI images of the knee joint. An analysis of modern deep computer vision architectures for feature extraction from MRI images is presented. This analysis was used to create applied architectures of machine learning models. These models are aimed at automating the process of diagnosing knee injuries in medical devices and systems. This work is devoted to different types of feature detection framework networks for machine learning architectures that perform magnetic resonance imaging (MRI) image classification of the knee. The resulting models were evaluated on the MRNet validation dataset, calculating the metrics (ROC-AUC), prediction accuracy, F1 score, and Cohen’s K-Kappa. The results of this work also show that Cohen's Kappa metric is important for evaluating models on the MRNet architecture because it provides a deeper understanding of the classification decisions of each model.
{"title":"Analysis of framework networks for sign detection in deep learning models","authors":"Pavlo Pukach","doi":"10.23939/sisn2022.12.169","DOIUrl":"https://doi.org/10.23939/sisn2022.12.169","url":null,"abstract":"This paper analyzes and compares modern deep learning models for the classification of MRI images of the knee joint. An analysis of modern deep computer vision architectures for feature extraction from MRI images is presented. This analysis was used to create applied architectures of machine learning models. These models are aimed at automating the process of diagnosing knee injuries in medical devices and systems. This work is devoted to different types of feature detection framework networks for machine learning architectures that perform magnetic resonance imaging (MRI) image classification of the knee. The resulting models were evaluated on the MRNet validation dataset, calculating the metrics (ROC-AUC), prediction accuracy, F1 score, and Cohen’s K-Kappa. The results of this work also show that Cohen's Kappa metric is important for evaluating models on the MRNet architecture because it provides a deeper understanding of the classification decisions of each model.","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":"130011299","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/sisn2022.12.230
Nazar Borovets, M. Bublyk, L. Chyrun
In work, a web application was designed and developed to support interaction between members of different households regarding the disposal of household waste and the sale of used goods on the secondary market. To minimize the negative human impact on the environment, the developed information system to support household waste disposal is based on the principles of a circular economy, where all available resources are reusable, goods to recycle, and in general, the level of consumption is reduced. The need to form the average consumer’s interest in finding a target audience for the distribution process on the secondary market of used goods is substantiated. The main distinguishing feature of the web application is providing consumers with an electronic platform that would provide an opportunity to successfully realize the need for sorted garbage (household waste, recyclables, etc.) with economic benefits for all participants of the interaction. As a result of the task, we carried out an analysis of knowledge in the direction of household waste disposal and existing applications to support circular economy processes. According to the compiled requirements specification, we used the TypeScript programming language, the React library, the SASS scripting metalanguage, and the MVC architecture. To ensure the correct operation of the service, manual, modular and automated testing was carried out. The developed software product has a simple interface. It is easy to use for every user who has access to the Internet and a desire to obtain additional resources in the difficult time of Ukraine’s military economy.
{"title":"Information support system for household waste disposal processes","authors":"Nazar Borovets, M. Bublyk, L. Chyrun","doi":"10.23939/sisn2022.12.230","DOIUrl":"https://doi.org/10.23939/sisn2022.12.230","url":null,"abstract":"In work, a web application was designed and developed to support interaction between members of different households regarding the disposal of household waste and the sale of used goods on the secondary market. To minimize the negative human impact on the environment, the developed information system to support household waste disposal is based on the principles of a circular economy, where all available resources are reusable, goods to recycle, and in general, the level of consumption is reduced. The need to form the average consumer’s interest in finding a target audience for the distribution process on the secondary market of used goods is substantiated. The main distinguishing feature of the web application is providing consumers with an electronic platform that would provide an opportunity to successfully realize the need for sorted garbage (household waste, recyclables, etc.) with economic benefits for all participants of the interaction. As a result of the task, we carried out an analysis of knowledge in the direction of household waste disposal and existing applications to support circular economy processes. According to the compiled requirements specification, we used the TypeScript programming language, the React library, the SASS scripting metalanguage, and the MVC architecture. To ensure the correct operation of the service, manual, modular and automated testing was carried out. The developed software product has a simple interface. It is easy to use for every user who has access to the Internet and a desire to obtain additional resources in the difficult time of Ukraine’s military economy.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"235 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":"116864077","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/sisn2022.12.208
Tianyuan Cui
In recent years, mobile edge computing and deep learning have attracted strong industry attention in the application scenario of autonomous driving. Mobile edge computing reduces the transmission delay of autonomous driving information by offloading computational tasks to edge servers to reduce the network load; deep learning can effectively improve the accuracy of obstacle detection, thereby enhancing the stability and safety of autonomous driving. This paper first introduces the basic concept and reference architecture of MEC and the commonly used model algorithms in deep learning, and then summarizes the applications of MEC and deep learning in autonomous driving from three aspects: target detection, path planning, and collision avoidance, and finally discusses and outlooks the problems and challenges in current research.
{"title":"Overview of deep learning and mobile edge computing in autonomous driving","authors":"Tianyuan Cui","doi":"10.23939/sisn2022.12.208","DOIUrl":"https://doi.org/10.23939/sisn2022.12.208","url":null,"abstract":"In recent years, mobile edge computing and deep learning have attracted strong industry attention in the application scenario of autonomous driving. Mobile edge computing reduces the transmission delay of autonomous driving information by offloading computational tasks to edge servers to reduce the network load; deep learning can effectively improve the accuracy of obstacle detection, thereby enhancing the stability and safety of autonomous driving. This paper first introduces the basic concept and reference architecture of MEC and the commonly used model algorithms in deep learning, and then summarizes the applications of MEC and deep learning in autonomous driving from three aspects: target detection, path planning, and collision avoidance, and finally discusses and outlooks the problems and challenges in current research.","PeriodicalId":444399,"journal":{"name":"Vìsnik Nacìonalʹnogo unìversitetu \"Lʹvìvsʹka polìtehnìka\". Serìâ Ìnformacìjnì sistemi ta merežì","volume":"55 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":"127111220","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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