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Traffic congestion propagation identification method in smart cities 智慧城市交通拥堵传播识别方法
IF 1.1
Infocommunications Journal Pub Date : 2021-01-01 DOI: 10.36244/ICJ.2021.1.6
A. Nagy, V. Simon
{"title":"Traffic congestion propagation identification method in smart cities","authors":"A. Nagy, V. Simon","doi":"10.36244/ICJ.2021.1.6","DOIUrl":"https://doi.org/10.36244/ICJ.2021.1.6","url":null,"abstract":"Managing the frequent traffic congestion (traffic jams) of the road networks of large cities is a major challenge for municipal traffic management organizations. In order to manage these situations, it is crucial to understand the processes that lead to congestion and propagation, because the occurrence of a traffic jam does not merely paralyze one street or road, but could spill over onto the whole vicinity (even an entire neighborhood). Solutions can be found in professional literature, but they either oversimplify the problem, or fail to provide a scalable solution. In this article, we describe a new method that not only provides an accurate road network model, but is also a scalable solution for identifying the direction of traffic congestion propagation. Our method was subjected to a detailed performance analysis, which was based on real road network data. According to testing, our method outperforms the ones that have been used to date.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"114 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88034802","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}
引用次数: 9
AutoML for Log File Analysis (ALFA) in a Production Line System of Systems pointed towards Predictive Maintenance 面向预测性维护的生产线系统日志文件自动分析(ALFA)
IF 1.1
Infocommunications Journal Pub Date : 2021-01-01 DOI: 10.36244/icj.2021.3.8
Matthias Maurer, A. Festl, Bor Bricelj, G. Schneider, Michael Schmeja
{"title":"AutoML for Log File Analysis (ALFA) in a Production Line System of Systems pointed towards Predictive Maintenance","authors":"Matthias Maurer, A. Festl, Bor Bricelj, G. Schneider, Michael Schmeja","doi":"10.36244/icj.2021.3.8","DOIUrl":"https://doi.org/10.36244/icj.2021.3.8","url":null,"abstract":"Automated machine learning and predictive maintenance have both become prominent terms in recent years. Combining these two fields of research by conducting log analysis using automated machine learning techniques to fuel predictive maintenance algorithms holds multiple advantages, especially when applied in a production line setting. This approach can be used for multiple applications in the industry, e.g., in semiconductor, automotive, metal, and many other industrial applications to improve the maintenance and production costs and quality. In this paper, we investigate the possibility to create a predictive maintenance framework using only easily available log data based on a neural network framework for predictive maintenance tasks. We outline the advantages of the ALFA (AutoML for Log File Analysis) approach, which are high efficiency in combination with a low entry border for novices, among others. In a production line setting, one would also be able to cope with concept drift and even with data of a new quality in a gradual manner. In the presented production line context, we also show the superior performance of multiple neural networks over a comprehensive neural network in practice. The proposed software architecture allows not only for the automated adaption to concept drift and even data of new quality but also gives access to the current performance of the used neural networks.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"46 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76341656","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}
引用次数: 3
A Survey on Machine Learning based Smart Maintenance and Quality Control Solutions 基于机器学习的智能维护和质量控制解决方案综述
IF 1.1
Infocommunications Journal Pub Date : 2021-01-01 DOI: 10.36244/icj.2021.4.4
Attila Frankó, P. Varga
{"title":"A Survey on Machine Learning based Smart Maintenance and Quality Control Solutions","authors":"Attila Frankó, P. Varga","doi":"10.36244/icj.2021.4.4","DOIUrl":"https://doi.org/10.36244/icj.2021.4.4","url":null,"abstract":"Machine learning aided tasks and processes have key roles in smart manufacturing, especially in controlling production and assembly lines, as well as smart maintenance and intelligent quality control. The last two ones are those tasks that nowadays are still performed manually by employees; however, there are numerous machine learning-based solutions that can automate these fields to optimize cost and performance. In this paper, we present an overview of smart manufacturing ecosystem and define the roles of maintenance and quality control in it. Up-to-date machine learning-based smart solutions will also be detailed while addressing current challenges and identifying hot research topics and possible gaps.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"228 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78607298","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}
引用次数: 4
Demonstrating BB84 Quantum Key Distribution in the Physical Layer of an Optical Fiber Based System 基于光纤的系统物理层BB84量子密钥分配演示
IF 1.1
Infocommunications Journal Pub Date : 2021-01-01 DOI: 10.36244/icj.2021.3.5
Márton Czermann, Péter Trócsányi, Z. Kis, Benedek Kovács, L. Bacsardi
{"title":"Demonstrating BB84 Quantum Key Distribution in the Physical Layer of an Optical Fiber Based System","authors":"Márton Czermann, Péter Trócsányi, Z. Kis, Benedek Kovács, L. Bacsardi","doi":"10.36244/icj.2021.3.5","DOIUrl":"https://doi.org/10.36244/icj.2021.3.5","url":null,"abstract":"Nowadays, widely spread encryption methods (e.g., RSA) and protocols enabling digital signatures (e.g., DSA, ECDSA) are an integral part of our life. Although recently developed quantum computers have low processing capacity, huge dimensions and lack of interoperability, we must underline their practical significance – applying Peter Shor’s quantum algorithm (which makes it possible to factorize integers in polynomial time) public key cryptography is set to become breakable. As an answer, symmetric key cryptography proves to be secure against quantum based attacks and with it quantum key distribution (QKD) is going through vast development and growing to be a hot topic in data security. This is due to such methods securely generating symmetric keys by protocols relying on laws of quantum physics.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"43 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73568883","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}
引用次数: 2
Processing and Visualizing the Low Earth Orbit Radio Frequency Spectrum Measurement Results From the SMOG Satellite Project SMOG卫星近地轨道射频频谱测量结果的处理与可视化
IF 1.1
Infocommunications Journal Pub Date : 2021-01-01 DOI: 10.36244/ICJ.2021.1.3
Donát Takács, Boldizsár Markotics, L. Dudás
{"title":"Processing and Visualizing the Low Earth Orbit Radio Frequency Spectrum Measurement Results From the SMOG Satellite Project","authors":"Donát Takács, Boldizsár Markotics, L. Dudás","doi":"10.36244/ICJ.2021.1.3","DOIUrl":"https://doi.org/10.36244/ICJ.2021.1.3","url":null,"abstract":"December 6, 2019, the second and third Hungarian satellites, SMOG-P and ATL-1 (both having been developed at the Budapest University of Technology and Economics) were launched. They both had a radio frequency spectrum analyzer on board, which was used to measure for the first time the strength of radio frequency signals radiated into space by terrestrial digital TV transmitters – that can be detected in orbit around the Earth. In this paper, we present how two- and three-dimensional radiosmog maps were created from raw data received from space. The goal of this paper is to demonstrate the process of creating these maps from the raw data collected; the analysis of the results visible in these maps is beyond the scope of the present discussion.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"40 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74196818","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}
引用次数: 4
Transient-based automatic incident detection method for intelligent transport systems 基于瞬态的智能交通系统事件自动检测方法
IF 1.1
Infocommunications Journal Pub Date : 2021-01-01 DOI: 10.36244/icj.2021.3.1
A. Nagy, Bernát Wiandt, V. Simon
{"title":"Transient-based automatic incident detection method for intelligent transport systems","authors":"A. Nagy, Bernát Wiandt, V. Simon","doi":"10.36244/icj.2021.3.1","DOIUrl":"https://doi.org/10.36244/icj.2021.3.1","url":null,"abstract":"One of the major problems of traffic in big cities today is the occurrence of congestion phenomena on the road network, which has several serious effects not only on the lives of drivers, but also on city inhabitants. In order to deal with these phenomena, it is essential to have an in-depth understanding of the processes that lead to the occurrence of congestion and its spilling over into contiguous areas of the city.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"85 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83883125","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}
引用次数: 1
Traffic Swarm Behaviour: Machine Learning and Game Theory in Behaviour Analysis 交通群行为:行为分析中的机器学习和博弈论
IF 1.1
Infocommunications Journal Pub Date : 2021-01-01 DOI: 10.36244/icj.2021.4.3
Gergely Hollósi, Csaba Lukovszki, Máté Bancsics, G. Magyar
{"title":"Traffic Swarm Behaviour: Machine Learning and Game Theory in Behaviour Analysis","authors":"Gergely Hollósi, Csaba Lukovszki, Máté Bancsics, G. Magyar","doi":"10.36244/icj.2021.4.3","DOIUrl":"https://doi.org/10.36244/icj.2021.4.3","url":null,"abstract":"High density traffic on highways and city streets consists of endless interactions among participants. These interactions and the corresponding behaviours have great impact not only on throughput of traffic but also on safety, comfort and economy. Because of this, there is a great interest in deeper understanding of these interactions and concluding the impacts on traffic participants. This paper explores and maps the world of traffic behaviour analysis, especially researches focusing on groups of vehicles called traffic swarm, while presents the state-of-the-art methods and algorithms. The conclusion of this paper states that there are special areas of traffic behaviour analysis which have great research potential in the near future to describe traffic behaviour in more detail than present methods.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"135 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79071590","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}
引用次数: 0
Sidecar based resource estimation method for virtualized environments 基于Sidecar的虚拟化环境资源估计方法
IF 1.1
Infocommunications Journal Pub Date : 2020-01-01 DOI: 10.36244/icj.2020.2.1
Csaba Simon, M. Maliosz, M. Máté, David Balla, Kristóf Torma
{"title":"Sidecar based resource estimation method for virtualized environments","authors":"Csaba Simon, M. Maliosz, M. Máté, David Balla, Kristóf Torma","doi":"10.36244/icj.2020.2.1","DOIUrl":"https://doi.org/10.36244/icj.2020.2.1","url":null,"abstract":"The widespread use of virtualization technologies in telecommunication system resulted in series of benefits, as flexibility, agility and increased resource usage efficiency. Nevertheless, the use of Virtualized Network Functions (VNF) in virtualized modules (e.g., containers, virtual machines) also means that some legacy mechanisms that are crucial for a telco grade operation are no longer efficient. Specifically, the monitoring of the resource sets (e.g., CPU power, memory capacity) allocated to VNFs cannot rely anymore on the methods developed for earlier deployment scenarios. Even the recent monitoring solutions designed for cloud environments is rendered useless if the VNF vendor and the telco solution supplier has to deploy its product into a virtualized environment, since it does not have access to the host level monitoring tools. In this paper we propose a sidecar-based solution to evaluate the resources available for a virtualized process. We evaluated the accuracy of our proposal in a proof of concept deployment, using KVM, Docker and Kubernetes virtualization technologies, respectively. We show that our proposal can provide real monitoring data and discuss its applicability.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"274 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73287204","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}
引用次数: 2
Graph construction with condition-based weights for spectral clustering of hierarchical datasets 基于条件权重的分层数据集谱聚类图构建
IF 1.1
Infocommunications Journal Pub Date : 2020-01-01 DOI: 10.36244/icj.2020.2.5
Dávid Papp, Zsolt Knoll, G. Szűcs
{"title":"Graph construction with condition-based weights for spectral clustering of hierarchical datasets","authors":"Dávid Papp, Zsolt Knoll, G. Szűcs","doi":"10.36244/icj.2020.2.5","DOIUrl":"https://doi.org/10.36244/icj.2020.2.5","url":null,"abstract":"Most of the unsupervised machine learning algorithms focus on clustering the data based on similarity metrics, while ignoring other attributes, or perhaps other type of connections between the data points. In case of hierarchical datasets, groups of points (point-sets) can be defined according to the hierarchy system. Our goal was to develop such spectral clustering approach that preserves the structure of the dataset throughout the clustering procedure. The main contribution of this paper is a set of conditions for weighted graph construction used in spectral clustering. Following the requirements – given by the set of conditions – ensures that the hierarchical formation of the dataset remains unchanged, and therefore the clustering of data points imply the clustering of point-sets as well. The proposed spectral clustering algorithm was tested on three datasets, the results were compared to baseline methods and it can be concluded the algorithm with the proposed conditions always preserves the hierarchy structure.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"4 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76474967","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}
引用次数: 0
Hybrid Distance-based, CNN and Bi-LSTM System for Dictionary Expansion 基于距离、CNN和Bi-LSTM的词典扩展混合系统
IF 1.1
Infocommunications Journal Pub Date : 2020-01-01 DOI: 10.36244/ICJ.2020.4.2
Béla Benedek Szakács, T. Mészáros
{"title":"Hybrid Distance-based, CNN and Bi-LSTM System for Dictionary Expansion","authors":"Béla Benedek Szakács, T. Mészáros","doi":"10.36244/ICJ.2020.4.2","DOIUrl":"https://doi.org/10.36244/ICJ.2020.4.2","url":null,"abstract":"Dictionaries like Wordnet can help in a variety of Natural Language Processing applications by providing additional morphological data. They can be used in Digital Humanities research, building knowledge graphs and other applications. Creating dictionaries from large corpora of texts written in a natural language is a task that has not been a primary focus of research, as other tasks have dominated the field (such as chat-bots), but it can be a very useful tool in analysing texts. Even in the case of contemporary texts, categorizing the words according to their dictionary entry is a complex task, and for less conventional texts (in old or less researched languages) it is even harder to solve this problem automatically. Our task was to create a software that helps in expanding a dictionary containing word forms and tagging unprocessed text. We used a manually created corpus for training and testing the model. We created a combination of Bidirectional Long-Short Term Memory networks, convolutional networks and a distancebased solution that outperformed other existing solutions. While manual post-processing for the tagged text is still needed, it significantly reduces the amount of it.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"57 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87217249","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}
引用次数: 0
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