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Journal articles on the topic 'Mobile communication systems Forecasting'

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Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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1

Павликов, С. Н., Е. Ю. Копаева, Ю. Ю. Колесов, П. Н. Петров, and М. А. Гареева. "Method of mobile radio communication." MORSKIE INTELLEKTUAL`NYE TEHNOLOGII)</msg>, no. 3(57) (August 7, 2022): 282–87. http://dx.doi.org/10.37220/mit.2022.57.3.036.

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Развитие морских интеллектуальных систем и их телекоммуникационного оборудования в ближайшее время будет происходить в условиях обострения проблем, связанных с: ростом уровня помех; повышенных требований к удельной пропускной способности; ограничений на ресурсы связи, сокращение допустимого времени реакции на изменение условий среды связи и взаимодействия носителей телекоммуникационного оборудования в ближней зоне. В работе предлагается новый способ мобильной связи, учитывающий перечисленные факторы. Целью работы является сокращение времени реакции радиосети на изменение условий при выполнении хэндовера и роуминга. Задача предусматривает анализ технологий подвижной радиосвязи. Вопрос развития особенно остро стоит для морского транспорта в условиях интенсивного движения в проливах, когда требуется интеллектуальный помощник в выработке вариантов управленческого решения во взаимодействии по технологии V2X. Статья посвящена поиску направлений по совершенствованию мобильной связи на морском транспорте. Актуальность связана с возрастанием скоростей носителей абонентов, интенсивности движения и отсутствием новых потенциальных возможностей по наращиванию пропускной способности телекоммуникационных систем. Метод решения поставленных задач основан на анализе развития и прогнозировании требований к мобильной радиосвязи. Новизна заключается в построении инициатором виртуальной мобильной сети, собираемой из доступных радиосистем связи на время решаемой задачи. Основные выводы: достигнут новый технический результат - сокращение времени реакции радиосети на изменение условий и ограничений работы мобильной радиосвязи. The development of marine intelligent systems and their telecommunications equipment in the near future will occur in the conditions of aggravation of problems associated with: the growth of the level of interference; increased requirements for specific throughput; restrictions on communication resources, reduction of the permissible reaction time to changes in the conditions of the communication environment and the interaction of telecommunication equipment carriers in the near zone. The paper proposes a new method of mobile communication, taking into account the listed factors. The aim of the work is to reduce the reaction time of the radio network to changes in conditions when performing handling and roaming. The task involves the analysis of known mobile radio communication technologies. The issue of development is especially acute for maritime transport in conditions of heavy traffic in the straits, when an intelligent assistant is required in the development of management solution options in interaction with V2X technology with available facilities and infrastructure. The article is devoted to the search for directions for improving mobile communication in maritime transport. The relevance is associated with an increase in the speed of subscriber carriers, traffic intensity and the lack of new potential opportunities to increase the capacity of telecommunication systems. The aim of the work is to reduce the reaction time of the radio network to changes in conditions when performing handling and roaming. The task involves the analysis of known mobile radio communication technologies. The issue of development is especially acute for maritime transport in conditions of heavy traffic in the straits, when an intelligent assistant is required in the development of management solution options in interaction with V2X technology with available facilities and infrastructure. The article is devoted to the search for directions for improving mobile communication in maritime transport. The relevance is associated with an increase in the speed of subscriber carriers, traffic intensity and the lack of new potential opportunities to increase the capacity of telecommunication systems. The method of solving the tasks is based on the analysis of the development and forecasting of requirements for mobile radio communication. The novelty lies in the construction by the initiator of a virtual mobile network assembled from available radio communication systems at the time of the task being solved. The main conclusions A new technical result has been achieved - reduction of the reaction time of the radio network to changes in the conditions and restrictions of mobile radio communication.
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2

Brožová, Helena, and Miroslav Růžička. "THE PREDICTION OF PARKING SPACE AVAILABILITY." Transport 35, no. 5 (December 21, 2020): 462–73. http://dx.doi.org/10.3846/transport.2020.14016.

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Intelligent Parking Systems (IPS) allow customers to select a car park according to their preferences, rapidly park their vehicle without searching for the available parking space (place) or even book their place in advance avoiding queues. IPS provides the possibility to reduce the wastage of fuel (energy) while finding a parking place and consequently reduce harmful emissions. Some systems interact with in-vehicle navigation systems and provide users with information in real-time such as free places available at a given parking lot (car park), the location and parking fees. Few of these systems, however, provide information on the forecasted utilisation at specific time. This paper describes results of a traffic survey carried out at the parking lot of supermarket and the proposal of the model predicting real-time parking space availability based on these surveyed data. The proposed model is formulated as the non-homogenous Markov chains that are used as a tool for the forecasting of parking space availability. The transition matrices are calculated for different time periods, which allow for and include different drivers’ behaviour and expectations. The proposed forecasting model is adequate for potential use by IPS with the support of different communication means such as the internet, navigation systems (GPS, Galileo etc.) and personal communication services (mobile-phones).
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3

Oprea, Mihaela, Vasile Buruiana, and Alexandra Matei. "A Microcontroller-based Intelligent System for Real-time Flood Alerting." International Journal of Computers Communications & Control 5, no. 5 (December 1, 2010): 844. http://dx.doi.org/10.15837/ijccc.2010.5.2245.

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The development of efficient flood alerting systems became more demanding in the last years. In this paper it is presented the first version of a prototype intelligent system for flood forecasting and real-time alerting. The system is implemented by using a microcontroller from the ARM family, Marvell 88F6281, and has a user interface realized under the Free UnixBSD operating system. Also, a knowledge base is integrated in the system. The real-time alert is sent to the decision making factors via a communication channel (such as, the internet, a mobile phone, or radio communication). Some experimental results obtained so far are also discussed in the paper.
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Pavlikov, S. N., E. Yu Kopaeva, Yu Yu Kolesov, and A. N. Kryuchkov. "TECHNOLOGIES FOR THE DEVELOPMENT OF MARINE INTEGRATED COMMUNICATION SYSTEMS." H&ES Research 14, no. 4 (2022): 19–25. http://dx.doi.org/10.36724/2409-5419-2022-14-4-19-25.

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The goal is to improve the quality of information interaction of objects by increasing the reliability of message delivery to recipients and bandwidth through the integration of networks using various signals and physical channels. A search for new technical solutions for the creation of integrated (hybrid) communication technologies aimed at expanding the possibilities for creating adaptive, self organizing, resistant to destabilizing factors communication systems with an increased quality of services provided in vast areas was carried out. The method of solving the tasks is based on the analysis of development trends and forecasting the requirements for integrated mobile communication systems. The novelty lies in the development and evaluation of options for building the structures of integrated communication systems, represented by diverse, complementary subsystems using various methods of channel separation, including in physical environments, as well as algorithms for their operation. Key findings. A set of technologies for the development of coastal integrated communication systems has been developed: the structure of the system based on a hybrid mesh topology; the basic form of the carrier signal with controlled parameters depending on the physical channel; the principle of control of orthogonal signals in adjacent channels of switching and relay nodes, as well as between network nodes; hydroacoustic communication method. Hydroacoustic communication for coastal areas is a potential for increasing the number of simultaneously used information channels per unit of the volume of interaction of vital objects and makes it possible to connect satellite, air, surface, underwater and bottom subsystems of telecommunications. The con ducted studies have shown the stability of the proposed methods in conditions of excess of interference over the signal.
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5

Gruenwald, Hermann. "Logistics Information Systems (LIS) on the Go-Mobile Apps and Social Media." Information Management and Business Review 7, no. 4 (August 30, 2015): 64–73. http://dx.doi.org/10.22610/imbr.v7i4.1164.

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Logistics has evolved over the past few decades from transportation and warehousing to global Supply Chain Management (SCM). This requires the coordination of the flow of material, money and information. The velocity of doing business has increased and manual operations have been automated. Modern Logistic Information Systems (LIS) with all its logistics related sub systems are replacing muscle power with brain power and pencil and paper with smart phones and social media. The virtual aspect of logistics has become equally important to the physical realm of transportation and warehousing. Supply Chain Management (SCM) deals with getting the right stuff to the right people at the right time in the right amount. To accomplish this task there are a number of more or less integrated logistics software application. Demand forecasting models based on historical data from data marts and data warehouses with built in seasonality and pricing models. Load planning software to appropriately palletize, containerize and load trucks, trains and vessels. Route planning software with real time traffic and weather updates combined with Global Positioning Systems (GPS) to reduce transportation time and fuel costs. Warehouse Management Systems (WMS) to receive, put-away, store, receive and marshal the shipment. Electronic documents accompany the shipment from purchase order, letter of credit to customs clearing and back-haul charges. While these applications in the past have been mostly desktop applications used in the office at the management level, the move is to mobile applications. The footprint of LIS is getting smaller and is moving from the desktop to the Smartphone. At the core of any logistic information systems (LIS) is electronic communication. With the advent of the internet and social media personal communication has taken on other forms. With smart phones and tablets like the I-Phone and I-Pad e-commerce advanced to m-commerce. While technology enables the global supply chain, how do future logistics professionals feel about applying this cutting edge communication technology in their personal and professional lives? This quantitative study compares the aptitude of Thai logistics management students towards the use of social media and modern mobile telecommunication technology in their personal lives and in the context of professional use in connection with logistics information systems (LIS).
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6

Mejia, Jose, Alberto Ochoa-Zezzati, and Oliverio Cruz-Mejía. "Traffic Forecasting on Mobile Networks Using 3D Convolutional Layers." Mobile Networks and Applications 25, no. 6 (May 28, 2020): 2134–40. http://dx.doi.org/10.1007/s11036-020-01554-y.

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7

Acosta-Coll, Melisa, Andres Solano-Escorcia, Lilia Ortega-Gonzalez, and Ronald Zamora-Musa. "Forecasting and communication key elements for low-cost fluvial flooding early warning system in urban areas." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 5 (October 1, 2021): 4143. http://dx.doi.org/10.11591/ijece.v11i5.pp4143-4156.

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Fluvial flooding occurs when a river overspills its banks due to excessive rainfall, and it is the most common flood event. In urban areas, the increment of urbanization makes communities more susceptible to fluvial flooding since the excess of impervious surfaces reduced the natural permeable areas. As flood prevention strategies, early warning systems (EWS) are used to reduce damage and protect people, but key elements need to be selected. This manuscript proposes the monitoring instruments, communication protocols, and media to forecast and disseminate EWS alerts efficiently during fluvial floods in urban areas. First, we conducted a systematic review of different EWS architectures for fluvial floods in urban areas and identified that not all projects monitor the most important variables related to the formation of fluvial floods and most use communication protocols with high-energy consumption. ZigBee and LoRaWAN are the communication protocols with lower power consumption from the review, and to determine which technology has better performance in urban areas, two wireless sensor networks were deployed and simulated in two urban areas susceptible to fluvial floods using Radio Mobile software. The results showed that although Zigbee technology has better-received signal strength, the difference with LoRAWAN is lower than 2 dBm, but LoRaWAN has a better signal-to-noise ratio, power consumption, coverage, and deployment cost.
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Lin, Shiu-Shin, Kai-Yang Zhu, Jun-Yuan Wang, and Ying-Po Liao. "Integrating ANFIS and Qt Framework to Develop a Mobile-Based Typhoon Rainfall Forecasting System." Wireless Communications and Mobile Computing 2022 (May 14, 2022): 1–11. http://dx.doi.org/10.1155/2022/5248308.

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Machine learning methods such as Adaptive Network-Based Fuzzy Inference System (ANFIS) have been widely employed in intelligent urban storm water disaster warning for the purpose of smart city. However, there exists lack of research proposed for applying ANFIS and mobile application (App) to reach the purpose of smart city. In order to accomplish the goal, the study integrates ANFIS and Qt Framework to develop a Typhoon Rainfall Forecasting System to real-time typhoon rainfall forecast via a mobile device. The Service is first built by applying cluster analysis to typhoon data (Tamsui Weather Station of Taiwan) during June 1967 and November 2020 to classify the data into four groups and then applying the ANFIS to construct the Service with data in each group. The fuzzy rule of ANFIS is established by grid partition method. Both the Service and App employ Qt Framework as the cross-operating development tool, and the App is transformed to a smart mobile device App of different platforms. The simulated results show the following: (1) Taking the example of typhoon Nakri in group 1, the lowest root mean square error (7.898 mm) and the lowest computation time (178 sec) were obtained for training with 1000 steps and three membership functions. (2) Using the optimal parameters of the typhoon belonging to that group can obtain better prediction results. The developed typhoon rainfall forecasting system App in the supplementary information demonstrates that the user can use the smart mobile device for real-time typhoon forecasting at the most three hours ahead easily.
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Psaroudakis, Chrysostomos, Gavriil Xanthopoulos, Dimitris Stavrakoudis, Antonios Barnias, Vassiliki Varela, Ilias Gkotsis, Anna Karvouniari, et al. "Development of an Early Warning and Incident Response System for the Protection of Visitors from Natural Hazards in Important Outdoor Sites in Greece." Sustainability 13, no. 9 (May 4, 2021): 5143. http://dx.doi.org/10.3390/su13095143.

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Safety in touristic destinations is of utmost importance since tourists’ preferences change frequently in response to emerging threats. Natural hazards are a significant risk and, as such, they need to be considered in the effort for safe tourism. Services and systems monitoring and predicting extreme natural phenomena and disasters in sites of special tourist and cultural interest can lead to more effective risk management and incident response. This paper presents Xenios, a system under development in Greece that provides early warning and risk communication services via web-based and mobile phone applications. We present the user requirements analysis contacted, which led to the design of a modular system architecture through a formal Business Process Model procedure. Currently, early warning systems for wildfire, floods, and extreme weather events are offered, based on a fusion of information from satellite imagery, meteorological forecasts, and risk estimation models. Moreover, visitors’ dispersion monitoring via unmanned aerial vehicles (UAVs) and Wi-Fi connection signals is also offered, along with emergency response planning and ticketing system’s interfacing. The system is built around a modular architecture that permits the easy integration of new subsystems or other danger forecasting modules, depending on the site’s actual needs and limitations. Xenios also provides a mobile app for site visitors, which establishes a communication link for sending alarms, but also serves them with useful tourist information, so that they are encouraged to download and use the app. Finally, the opportunities for supporting a viable business model are also discussed. The results of this study could prove useful in designing other natural risk management systems for sites of cultural and natural interest.
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Duda, Oleksii, Liliana Dzhydzhora, Oleksandr Matsiuk, Andrii Stanko, Nataliia Kunanets, Volodymyr Pasichnyk, and Oksana Kunanets. "Mobile information system for monitoring the spread of viruses in smart cities." Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežì 8 (December 5, 2020): 65–70. http://dx.doi.org/10.23939/sisn2020.08.065.

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The concept of creating a multi-level mobile personalized system for fighting viral diseases, in particular Covid-19, was developed. Using the integration of the Internet of Things, Cloud Computing and Big Data technologies, the system involves a combination of two architectures: client-server and publication-subscription. The advantage of the system is the permanent help with viral diseases, namely on communication, information, and medical stages. The smart city concept in the context of viral disease control focuses on the application of Big Data analysis methods and the improvement of forecasting procedures and emergency treatment protocols. Using different technologies, cloud server stores the positioning data obtained from different devices, and the application accesses API to display and analyze the positioning data in real time. Due to the technologies combination, internal and external positioning can be used with a certain accuracy degree, being useful for various medical and emergency situations and analysis and the following processing by other smart city information systems. The result of the given investigation is the development of the conceptual model of multi-level mobile personalized health status monitoring system used for intellectual data analysis, prediction, treatment and prevention of viral diseases such as Covid-19 in modern “smart city”.
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Karsisto, Virve, and Lauri Lovén. "Verification of Road Surface Temperature Forecasts Assimilating Data from Mobile Sensors." Weather and Forecasting 34, no. 3 (May 9, 2019): 539–58. http://dx.doi.org/10.1175/waf-d-18-0167.1.

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ABSTRACT The advances in communication technologies have made it possible to gather road condition information from moving vehicles in real time. However, data quality must be assessed and its effects on the road weather forecasts analyzed before using the new data as input in forecasting systems. Road surface temperature forecasts assimilating mobile observations in the initialization were verified in this study. In addition to using measured values directly, different statistical corrections were applied to the mobile observations before using them in the road weather model. The verification results are compared to a control run without surface temperature measurements and to a control run that utilized interpolated values from surrounding road weather stations. Simulations were done for the period 12 October 2017–30 April 2018 for stationary road weather station points in southern Finland. Road surface temperature observations from the stations were used in the forecast verification. According to the results, the mobile observations improved the accuracy of road surface temperature forecasts when compared to the first control run. The statistical correction methods had a positive effect on forecast accuracy during the winter, but the effect varied during spring when the daily temperature variation was strong. In the winter season, the forecasts based on the interpolated road surface temperature values and the forecasts utilizing mobile observations with statistical correction had comparable accuracy. However, the tested area has high road weather station density and not much elevation variation, so results might have been different in more varying terrain.
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12

Tomala, Malgorzata, and Kamil Staniec. "Modelling of ML-Enablers in 5G Radio Access Network-Conceptual Proposal of Computational Framework." Electronics 12, no. 3 (January 17, 2023): 481. http://dx.doi.org/10.3390/electronics12030481.

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The fifth generation (5G) of mobile networks connects people, things, data, applications, transport systems, and cities in smart networked communication environments. With the growth in the amount of generated data, the number of wirelessly connected machines, traffic types, and associated requirements, ensuring high-quality mobile connectivity becomes incredibly difficult for technology suppliers. Mobile operators and network vendors enrolling in 5G face far more rapid demands than any technology before, and at the same time need to ensure efficiency and reliability in the network operations. In fact, intelligent forecasting and decision-making strategies are several of the centerpieces of current artificial intelligence research in various domains. Due to its strong fitting ability, machine learning is seen to have great potential to be employed to solve telecommunication networks’ optimization problems that range from the design of hardware elements to network self-optimization. This paper addresses the question of how to apply artificial intelligence to 5G radio access control and feed ML techniques with radio characteristic-based automatic data collection to achieve ML-based evaluation of 5G performance. The proposed methodology endorses ML tools for the 5G portfolio scenarios requirements assessment and integrates into the mature methods for network performance optimization: self-organizing networks (SON) and minimization of drive tests (MDT). In this context, the proposed treatment guides future network deployments and implementations adopted on a 3GPP standard basis.
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Xu, Fengli, Yuyun Lin, Jiaxin Huang, Di Wu, Hongzhi Shi, Jeungeun Song, and Yong Li. "Big Data Driven Mobile Traffic Understanding and Forecasting: A Time Series Approach." IEEE Transactions on Services Computing 9, no. 5 (September 1, 2016): 796–805. http://dx.doi.org/10.1109/tsc.2016.2599878.

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14

Fang, Luoyang, Xiang Cheng, Haonan Wang, and Liuqing Yang. "Mobile Demand Forecasting via Deep Graph-Sequence Spatiotemporal Modeling in Cellular Networks." IEEE Internet of Things Journal 5, no. 4 (August 2018): 3091–101. http://dx.doi.org/10.1109/jiot.2018.2832071.

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15

Cheng, Ding-Yuan, Chi-Hua Chen, Chia-Hung Hsiang, Chi-Chun Lo, Hui-Fei Lin, and Bon-Yeh Lin. "The Optimal Sampling Period of a Fingerprint Positioning Algorithm for Vehicle Speed Estimation." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/306783.

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Using cellular floating vehicle data is a crucial technique for measuring and forecasting real-time traffic information based on anonymously sampling mobile phone positions for intelligent transportation systems (ITSs). However, a high sampling frequency generates a substantial load for ITS servers, and traffic information cannot be provided instantly when the sampling period is long. In this paper, two analytical models are proposed to analyze the optimal sampling period based on communication behaviors, traffic conditions, and two consecutive fingerprint positioning locations from the same call and estimate vehicle speed. The experimental results show that the optimal sampling period is 41.589 seconds when the average call holding time was 60 s, and the average speed error rate was only 2.87%. ITSs can provide accurate and real-time speed information under lighter loads and within the optimal sampling period. Therefore, the optimal sampling period of a fingerprint positioning algorithm is suitable for estimating speed information immediately for ITSs.
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Mokhtari, Arian, Niloofar Ghorbani, and Behnam Bahrak. "Aggregated Traffic Anomaly Detection Using Time Series Forecasting on Call Detail Records." Security and Communication Networks 2022 (March 2, 2022): 1–9. http://dx.doi.org/10.1155/2022/1182315.

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Mobile network operators store an enormous amount of information like log files that describe various events and users’ activities. Analysis of these logs might be used in many critical applications such as detecting cyber attacks, finding behavioral patterns of users, security incident response, and network forensics. In a cellular network, call detail records (CDRs) is one type of such logs containing metadata of calls and usually includes valuable information about contacts such as the phone numbers of originating and receiving subscribers, call duration, the area of activity, type of call (SMS or voice call), and a timestamp. With anomaly detection, it is possible to determine abnormal reduction or increment of network traffic in an area or for a particular person. This paper’s primary goal is to study subscribers’ behavior in a cellular network, mainly predicting the number of calls in a region and detecting anomalies in the network traffic. In this paper, a new hybrid method is proposed based on various anomaly detection methods such as GARCH, K-means, and neural network to determine the anomalous data. Moreover, we have discussed the possible causes of such anomalies.
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Ali, Alisha, and Andrew J. Frew. "ICT and sustainable tourism development: an innovative perspective." Journal of Hospitality and Tourism Technology 5, no. 1 (March 11, 2014): 2–16. http://dx.doi.org/10.1108/jhtt-12-2012-0034.

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Purpose – The aim of this research is to foreground information and communication technology (ICT) as an innovative approach for sustainable tourism (ST) development of destinations. ICT is the technology required for information processing which facilitates data processing, information sharing, communication, searching and selection. This paper concentrates on the Abernathy and Clark model and its usefulness in applying ICT as innovative in managing ST. Design/methodology/approach – An online survey was administered to destination managers and to eTourism experts. Destination managers were selected as they were identified as the person responsible for the overall management of a Destination Management Organisation. eTourism experts were identified as someone who possesses special expertise, knowledge and skills on ICT applications to tourism and offered expertise on which ranged from such areas as electronic distribution, recommender systems, user-generated content, online communities, mobile technology, technology acceptance, tourism networks and Web 2.0. This was followed by semi-structured interviews. Findings – These ICT tools were found to be innovative for information management and distribution for critical decision-making. Innovation was fostered through the use of ICT for ST by leading to a better understanding of the tourism product, monitoring, measuring and evaluating, forecasting trends, developing partnerships and engaging and supporting stakeholder relationships. ICT would provide novel ways of approaching marketing, energy monitoring, waste management, and communication for destinations. Originality/value – This research is important in demonstrating the value that technology can have to ST and further develops the work on tourism innovation theory.
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Wang, Xin, Shuhui Chen, and Jinshu Su. "Real Network Traffic Collection and Deep Learning for Mobile App Identification." Wireless Communications and Mobile Computing 2020 (February 19, 2020): 1–14. http://dx.doi.org/10.1155/2020/4707909.

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The proliferation of mobile devices over recent years has led to a dramatic increase in mobile traffic. Demand for enabling accurate mobile app identification is coming as it is an essential step to improve a multitude of network services: accounting, security monitoring, traffic forecasting, and quality-of-service. However, traditional traffic classification techniques do not work well for mobile traffic. Besides, multiple machine learning solutions developed in this field are severely restricted by their handcrafted features as well as unreliable datasets. In this paper, we propose a framework for real network traffic collection and labeling in a scalable way. A dedicated Android traffic capture tool is developed to build datasets with perfect ground truth. Using our established dataset, we make an empirical exploration on deep learning methods for the task of mobile app identification, which can automate the feature engineering process in an end-to-end fashion. We introduce three of the most representative deep learning models and design and evaluate our dedicated classifiers, namely, a SDAE, a 1D CNN, and a bidirectional LSTM network, respectively. In comparison with two other baseline solutions, our CNN and RNN models with raw traffic inputs are capable of achieving state-of-the-art results regardless of TLS encryption. Specifically, the 1D CNN classifier obtains the best performance with an accuracy of 91.8% and macroaverage F-measure of 90.1%. To further understand the trained model, sample-specific interpretations are performed, showing how it can automatically learn important and advanced features from the uppermost bytes of an app’s raw flows.
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Aina, Folayo, Sufian Yousef, and Opeyemi Osanaiye. "Analysing admission control for AODV and DSR routing protocol in mobile ad-hoc network." Bulletin of Electrical Engineering and Informatics 10, no. 5 (October 1, 2021): 2667–77. http://dx.doi.org/10.11591/eei.v10i5.3171.

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The widespread deployment of mobile ad-hoc network (MANET) in the areas of agriculture, military defence, weather forecasting and disaster control has necessitated the implementation of admission control within a network for a guaranteed quality of service (QoS). Admission control organises traffic flows to ensure the network medium is fairly shared among various nodes in the network. Various admission control algorithms have been proposed in the literature, using different metrics and parameters to achieve different admission control quality. In this work, we propose an Admission control in mobile ad-hoc network routing (ACMANR) using both bandwidth capacity and resource estimation to achieve a good QoS. Furthermore, we analyse the behaviour of two well-known routing protocols in wireless network, ad hoc on-demand distance vector (AODV) and dynamic source routing (DSR), in our proposed admission control algorithm. Simulation results obtained from our proposed admission control algorithm using OPNET show that AODV routing protocol had a better throughput while DSR produced a better delay with lower overhead in MANET. Our proposed approach also shows better performance in terms of throughput and delay when compared with the state-of-the-art admission control routing using AODV and DSR.
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Gian, Quoc-Anh, Dinh-Chinh Nguyen, Duc-Nghia Tran, and Duc-Tan Tran. "Monitoring of Landslides in Mountainous Regions based on FEM Modelling and Rain Gauge Measurements." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (October 1, 2016): 2106. http://dx.doi.org/10.11591/ijece.v6i5.10482.

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<p><span>Vietnam is a country heavily influenced by climate change. The effect of climate change leads to a series of dangerous phenomena, such as landslides. Landslides occur not only in the mountainous province, but also in Delta provinces, where hundreds of landslides are reported annually in the North-Western provinces of Vietnam. These events have catastrophic impact to the community as well as the economy. In mountainous areas, the conditions for landslides to occur are met frequently, especially after heavy rains or geological activity, causing harm to the community as well as damaging or destroying much needed infrastructure and key transport routes. However, in Vietnam, investment in mountainous regions has been often lower than in urban areas. The meteorology monitoring and forecasting systems are ill equipped and overloaded, so they cannot deliver earlier and more accurate forecasts for complex weather events, unable to provide timely warnings. It can be seen that in countries that landslide often occur, researchers have been trying to develop low cost and efficient landslide detection system. This paper precisely addressed the problems mentioned, by designing and implementing an efficient and reliable Landslide Monitoring and Early Warning (LMnE) system based on the 3G/2G mobile communication system, and a rain gauge at the field site along with a carefully FEM (finite element method) simulation using the rain density information on the server. The system uses advanced processing algorithms combining obtained data at the central station.</span></p>
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Gian, Quoc-Anh, Dinh-Chinh Nguyen, Duc-Nghia Tran, and Duc-Tan Tran. "Monitoring of Landslides in Mountainous Regions based on FEM Modelling and Rain Gauge Measurements." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (October 1, 2016): 2106. http://dx.doi.org/10.11591/ijece.v6i5.pp2106-2113.

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<p><span>Vietnam is a country heavily influenced by climate change. The effect of climate change leads to a series of dangerous phenomena, such as landslides. Landslides occur not only in the mountainous province, but also in Delta provinces, where hundreds of landslides are reported annually in the North-Western provinces of Vietnam. These events have catastrophic impact to the community as well as the economy. In mountainous areas, the conditions for landslides to occur are met frequently, especially after heavy rains or geological activity, causing harm to the community as well as damaging or destroying much needed infrastructure and key transport routes. However, in Vietnam, investment in mountainous regions has been often lower than in urban areas. The meteorology monitoring and forecasting systems are ill equipped and overloaded, so they cannot deliver earlier and more accurate forecasts for complex weather events, unable to provide timely warnings. It can be seen that in countries that landslide often occur, researchers have been trying to develop low cost and efficient landslide detection system. This paper precisely addressed the problems mentioned, by designing and implementing an efficient and reliable Landslide Monitoring and Early Warning (LMnE) system based on the 3G/2G mobile communication system, and a rain gauge at the field site along with a carefully FEM (finite element method) simulation using the rain density information on the server. The system uses advanced processing algorithms combining obtained data at the central station.</span></p>
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Gijón, Carolina, Matías Toril, Salvador Luna-Ramírez, María Luisa Marí-Altozano, and José María Ruiz-Avilés. "Long-Term Data Traffic Forecasting for Network Dimensioning in LTE with Short Time Series." Electronics 10, no. 10 (May 12, 2021): 1151. http://dx.doi.org/10.3390/electronics10101151.

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Network dimensioning is a critical task in current mobile networks, as any failure in this process leads to degraded user experience or unnecessary upgrades of network resources. For this purpose, radio planning tools often predict monthly busy-hour data traffic to detect capacity bottlenecks in advance. Supervised Learning (SL) arises as a promising solution to improve predictions obtained with legacy approaches. Previous works have shown that deep learning outperforms classical time series analysis when predicting data traffic in cellular networks in the short term (seconds/minutes) and medium term (hours/days) from long historical data series. However, long-term forecasting (several months horizon) performed in radio planning tools relies on short and noisy time series, thus requiring a separate analysis. In this work, we present the first study comparing SL and time series analysis approaches to predict monthly busy-hour data traffic on a cell basis in a live LTE network. To this end, an extensive dataset is collected, comprising data traffic per cell for a whole country during 30 months. The considered methods include Random Forest, different Neural Networks, Support Vector Regression, Seasonal Auto Regressive Integrated Moving Average and Additive Holt–Winters. Results show that SL models outperform time series approaches, while reducing data storage capacity requirements. More importantly, unlike in short-term and medium-term traffic forecasting, non-deep SL approaches are competitive with deep learning while being more computationally efficient.
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Dmitriev, V. Ya, T. A. Ignat'eva, and V. P. Pilyavskiy. "Development of Artificial Intelligence and Prospects for Its Application." Economics and Management 27, no. 2 (May 1, 2021): 132–38. http://dx.doi.org/10.35854/1998-1627-2021-2-132-138.

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Aim. To analyze the concept of “artificial intelligence”, to justify the effectiveness of using artificial intelligence technologies.Tasks. To study the conceptual apparatus; to propose and justify the author’s definition of the “artificial intelligence” concept; to describe the technology of speech recognition using artificial intelligence.Methodology. The authors used such general scientific methods of cognition as comparison, deduction and induction, analysis, generalization and systematization.Results. Based on a comparative analysis of the existing conceptual apparatus, it is concluded that there is no single concept of “artificial intelligence”. Each author puts his own vision into it. In this regard, the author’s definition of the “artificial intelligence” concept is formulated. It is determined that an important area of applying artificial intelligence technologies in various fields of activity is speech recognition technology. It is shown that the first commercially successful speech recognition prototypes appeared already by the 1990s, and since the beginning of the 21st century. The great interest in “end-to-end” automatic speech recognition has become obvious. While traditional phonetic approaches have requested pronunciation, acoustic, and language model data, end-to-end models simultaneously consider all components of speech recognition, thereby facilitating the stages of self-learning and development. It is established that a significant increase in the” mental “ capabilities of computer technology and the development of new algorithms have led to new achievements in this direction. These advances are driven by the growing demand for speech recognition.Conclusions. According to the authors, artificial intelligence is a complex of computer programs that duplicate the functions of the human brain, opening up the possibility of informal learning based on big data processing, allowing to solve the problems of pattern recognition (text, image, speech) and the formation of management decisions. Currently, the active development of information and communication technologies and artificial intelligence concepts has led to a wide practical application of intelligent technologies, especially in control systems. The impact of these systems can be found in the work of mobile phones and expert systems, in forecasting and other areas. Among the obstacles to the development of this technology is the lack of accuracy in speech and voice recognition systems in the conditions of sound interference, which is always present in the external environment. However, the recent advances overcome this disadvantage.
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Li, Chengfan, Lan Liu, Junjuan Zhao, and Yuejun Liu. "An Experiment to Design an Operation and Maintenance System Integrating Apriori Association Rules for a Telecom Platform." Wireless Communications and Mobile Computing 2021 (September 30, 2021): 1–14. http://dx.doi.org/10.1155/2021/1185584.

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The operation and maintenance management of telecom platforms puts more emphasis on operation and alarm monitoring and less on business flow, and it is difficult to have a seamless connection between operation and maintenance and sales. To improve the cooperative efficiency and the informatization level of telecom platform operation and maintenance, a new operation and maintenance system integrating Apriori association rules for a telecom platform is proposed. In this paper, the Apriori algorithm is firstly used to analyse the fault correlation of the operation and maintenance system of the telecommunications platform to get the alarm message. Then, the fault risk of the operation and maintenance platform is evaluated intelligently by the system-business alarm causality model. Finally, based on the fixed end and the mobile end, the dynamic presentation of the system running state and alarm monitoring, device query and positioning, and online and offline inspection are implemented and designed, respectively. Experimental results show that the proposed operation and maintenance systems integrating Apriori association rules for the telecom platform innovate the cooperative mode between the operations and sales team, and the average time reduces to 3.9 minutes from 4.7 minutes and the risk forecasting accuracy increases from 8% to 26%. The assumed method can significantly improve the operational efficiency and intelligent level of the telecom platform’s system and business.
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25

Ramsdale, P. A. "Mobile Communication Systems." Electronics & Communications Engineering Journal 2, no. 2 (1990): 43. http://dx.doi.org/10.1049/ecej:19900012.

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26

Mazhar, Tehseen, Hafiz Muhammad Irfan, Inayatul Haq, Inam Ullah, Madiha Ashraf, Tamara Al Shloul, Yazeed Yasin Ghadi, Imran, and Dalia H. Elkamchouchi. "Analysis of Challenges and Solutions of IoT in Smart Grids Using AI and Machine Learning Techniques: A Review." Electronics 12, no. 1 (January 3, 2023): 242. http://dx.doi.org/10.3390/electronics12010242.

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With the assistance of machine learning, difficult tasks can be completed entirely on their own. In a smart grid (SG), computers and mobile devices may make it easier to control the interior temperature, monitor security, and perform routine maintenance. The Internet of Things (IoT) is used to connect the various components of smart buildings. As the IoT concept spreads, SGs are being integrated into larger networks. The IoT is an important part of SGs because it provides services that improve everyone’s lives. It has been established that the current life support systems are safe and effective at sustaining life. The primary goal of this research is to determine the motivation for IoT device installation in smart buildings and the grid. From this vantage point, the infrastructure that supports IoT devices and the components that comprise them is critical. The remote configuration of smart grid monitoring systems can improve the security and comfort of building occupants. Sensors are required to operate and monitor everything from consumer electronics to SGs. Network-connected devices should consume less energy and be remotely monitorable. The authors’ goal is to aid in the development of solutions based on AI, IoT, and SGs. Furthermore, the authors investigate networking, machine intelligence, and SG. Finally, we examine research on SG and IoT. Several IoT platform components are subject to debate. The first section of this paper discusses the most common machine learning methods for forecasting building energy demand. The authors then discuss IoT and how it works, in addition to the SG and smart meters, which are required for receiving real-time energy data. Then, we investigate how the various SG, IoT, and ML components integrate and operate using a simple architecture with layers organized into entities that communicate with one another via connections.
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27

Ludwin, W., and A. Jajszczyk. "Mobile Communication Systems [Book Review]." IEEE Communications Magazine 40, no. 5 (May 2002): 34. http://dx.doi.org/10.1109/mcom.2002.1000211.

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28

Hwang, F. K., and D. Shi. "Optimal relayed mobile communication systems." IEEE Transactions on Reliability 38, no. 4 (1989): 457–59. http://dx.doi.org/10.1109/24.46463.

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29

Norbury, J. R. "Satellite land mobile communication systems." Electronics & Communications Engineering Journal 1, no. 6 (1989): 245. http://dx.doi.org/10.1049/ecej:19890051.

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Puzmanova, Rita. "W-CDMA Mobile Communication Systems." Computer Communications 26, no. 12 (July 2003): 1427. http://dx.doi.org/10.1016/s0140-3664(03)00040-9.

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31

HIROMATSU, Yoshio, Naomaro HASHIMOTO, and Yoshinobu KOBAYASHI. "Navigation and new mobile communication systems." Journal of the Japan Society for Precision Engineering 55, no. 5 (1989): 818–21. http://dx.doi.org/10.2493/jjspe.55.818.

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32

Anikonov. "Optimal modernization of mobile communication systems." SPIIRAS Proceedings 2, no. 2 (March 17, 2014): 368. http://dx.doi.org/10.15622/sp.2.33.

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33

Dobroliubova, Maryna, Maryna Filippova, Dina Nevgod, and Maksym Kovalenko. "Automated verificationcomplex for mobile communication systems." MECHANICS OF GYROSCOPIC SYSTEMS, no. 38 (November 11, 2019): 78–90. http://dx.doi.org/10.20535/0203-3771382019203009.

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34

Pandya, R. "Emerging mobile and personal communication systems." IEEE Communications Magazine 33, no. 6 (June 1995): 44–52. http://dx.doi.org/10.1109/35.387549.

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35

Barnard, M., and S. McLaughlin. "Reconfigurable terminals for mobile communication systems." Electronics & Communication Engineering Journal 12, no. 6 (December 1, 2000): 281–92. http://dx.doi.org/10.1049/ecej:20000607.

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36

Oh, Sang-Yeob, Supratip Ghose, Hye-Jung Jang, and Kyungyong Chung. "Recent trends in Mobile Communication Systems." Journal of Computer Virology and Hacking Techniques 10, no. 2 (March 25, 2014): 67–70. http://dx.doi.org/10.1007/s11416-014-0213-z.

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37

Xiao, Zheng Rong, Li Yun Zhang, Jun Liao, and Bin Feng Yan. "Coexistence Studies between Mobile Communication Systems and Broadcasting Systems." Applied Mechanics and Materials 303-306 (February 2013): 2022–26. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2022.

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With the rapid development of mobile internet, more and more frequency band will be needed to meet the requirement of high data speed. The system coexistence between mobile system and broadcast system is studied, including the scenarios, models, simulation results, related analysis, and finally the solution to resolve the coexistence is given. In urban, an additional 37dB isolation between broadcast system and mobile base station should been satisfied. And an additional 15.7dB is needed between mobile base station and broadcast receiver.
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38

CHEN, Chien-Sheng, Szu-Lin SU, and Yih-Fang HUANG. "Mobile Location Estimation in Wireless Communication Systems." IEICE Transactions on Communications E94-B, no. 3 (2011): 690–93. http://dx.doi.org/10.1587/transcom.e94.b.690.

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39

Husar, Andrej, Peter Cepel, Peter Brida, and Vladimir Wieser. "Radio Resource Allocation in Mobile Communication Systems." Communications - Scientific letters of the University of Zilina 7, no. 4 (December 31, 2005): 66–68. http://dx.doi.org/10.26552/com.c.2005.4.66-68.

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40

Golikov, Alexandr, Vadim Gubanov, and Igor Garanzha. "Atypical structural systems for mobile communication towers." IOP Conference Series: Materials Science and Engineering 365 (June 2018): 052010. http://dx.doi.org/10.1088/1757-899x/365/5/052010.

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41

Sarkar, S., and K. N. Sivarajan. "Hypergraph models for cellular mobile communication systems." IEEE Transactions on Vehicular Technology 47, no. 2 (May 1998): 460–71. http://dx.doi.org/10.1109/25.669084.

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42

Anderson, S., M. Millnert, M. Viberg, and B. Wahlberg. "An adaptive array for mobile communication systems." IEEE Transactions on Vehicular Technology 40, no. 1 (February 1991): 230–36. http://dx.doi.org/10.1109/25.69993.

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43

Li, Ji, Jean Conan, and Samuel Pierre. "Mobile Terminal Location for MIMO Communication Systems." IEEE Transactions on Antennas and Propagation 55, no. 8 (August 2007): 2417–20. http://dx.doi.org/10.1109/tap.2007.901862.

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Anvekar, D. K., and S. S. Pradhan. "Handover scheme for mobile cellular communication systems." Electronics Letters 32, no. 11 (1996): 961. http://dx.doi.org/10.1049/el:19960665.

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Zahariadis, T., and D. Kazakos. "(R)evolution toward 4G mobile communication systems." IEEE Wireless Communications 10, no. 4 (August 2003): 6–7. http://dx.doi.org/10.1109/mwc.2003.1224973.

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Okumura, Yukihiko. "4. Error Control for Mobile Communication Systems." Journal of The Institute of Image Information and Television Engineers 70, no. 9 (2016): 754–63. http://dx.doi.org/10.3169/itej.70.754.

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Lim, Yujin, Hideyuki Takahashi, Fan Wu, and Rossana M. de Castro Andrade. "Challenges for the Future Mobile Communication Systems." Mobile Information Systems 2017 (2017): 1. http://dx.doi.org/10.1155/2017/1298659.

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KO, Y. C. "Doppler Spread Estimation in Mobile Communication Systems." IEICE Transactions on Communications E88-B, no. 2 (February 1, 2005): 724–28. http://dx.doi.org/10.1093/ietcom/e88-b.2.724.

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Ancans, Guntis, Vjaceslavs Bobrovs, Arnis Ancans, and Diana Kalibatiene. "Spectrum Considerations for 5G Mobile Communication Systems." Procedia Computer Science 104 (2017): 509–16. http://dx.doi.org/10.1016/j.procs.2017.01.166.

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Okaie, Yutaka. "Cluster Formation by Mobile Molecular Communication Systems." IEEE Transactions on Molecular, Biological and Multi-Scale Communications 5, no. 2 (November 2019): 153–57. http://dx.doi.org/10.1109/tmbmc.2020.2981662.

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