In recent years, Bluetooth beacons have been widely used in numerous application domains, including smart cities, assistive technologies, and intelligent transportation management. Researchers or developers associated...
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Privacy is an issue of concern in the electronic era where data has become a primary source of investment for businesses and organizations. The value generated from data is put to use in a number of ways for economic ...
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With a large collection of digital music in recent days, the challenge is to organize and access the music efficiently. Research in the field of Music Information Retrieval (MIR) focuses on these challenges. In this p...
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ISBN:
(纸本)9789813299498;9789813299481
With a large collection of digital music in recent days, the challenge is to organize and access the music efficiently. Research in the field of Music Information Retrieval (MIR) focuses on these challenges. In this paper, we develop a system which automatically identifies the instrument in a given Carnatic music on ten different types of instruments. We extract the well-known features namely, MFCC and LPC, and analyze the capability of these features in distinguishing different instruments. Then, we apply, the classification techniques like, Artificial Neural Network, Support Vector Machine, and Bayesian classifiers on those features. We compare the performances of those algorithms along with different features for Carnatic music instruments identification.
Traffic congestion is a critical problem in urban area. In this study, our objective is the control of traffic lights in an urban environment, in order to avoid traffic jams and optimize vehicle traffic;we aim to mini...
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ISBN:
(纸本)9781728180847
Traffic congestion is a critical problem in urban area. In this study, our objective is the control of traffic lights in an urban environment, in order to avoid traffic jams and optimize vehicle traffic;we aim to minimize the total waiting time. Our system is based on a new paradigm, which is deep reinforcement learning;it can automatically learn all the useful characteristics of traffic data and develop a strategy optimizing adaptive traffic light control. Our system is coupled to a microscopic simulator based on agents (Simulation of Urban MObility - SUMO) providing a synthetic but realistic environment in which the exploration of the results of potential regulatory actions can be carried out.
With the concept of lifelong education being widely recognized, people's demand for education and training is growing, and online education has gradually become one of the important ways for people to meet the nee...
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ISBN:
(纸本)9783030152352;9783030152345
With the concept of lifelong education being widely recognized, people's demand for education and training is growing, and online education has gradually become one of the important ways for people to meet the needs of education and training. Through analysis, it is found that online education also faces the development bottleneck of the lack of on-site teaching sense, systemic needs to be improved, the course completion rate is low, the quality of the course is difficult to guarantee, the teacher's teaching pressure is high, and lack of social recognition, which restricts the further development. With the help of current technology hotspots - big data and artificial intelligence, we can effectively break through the above bottlenecks and make the online education industry maintain rapid development. This paper analyzes the root causes of the problems in the current online education and discusses the solutions to improve online education.
The arrival of the IoT has benefited multiple industrial sectors;one of them is the electrical industry. It makes the IoT an attractive platform for the smart grid, because it improves the monitoring, analysis, availa...
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ISBN:
(纸本)9783030325237;9783030325220
The arrival of the IoT has benefited multiple industrial sectors;one of them is the electrical industry. It makes the IoT an attractive platform for the smart grid, because it improves the monitoring, analysis, availability, autonomy, and control of grid systems, from distribution to transmission. In this work, it is proposed the Electrical Internet of Things - EIoT, a platform for the data management in electrical systems. The EIoT platform relies on the LPWAN technologies to connect electrical things geographically distributed. This approach attempts to cover Fire Protection Systems in Substations, Control and Monitoring for the Demand Management, Electrical Asset Management, and intelligent Power Management and Monitoring in Refrigerators applications, but other smart grid applications fit as well. The EIoT platform implemented LoRa, a LPWAN technology, and its LoRaWAN protocol to connect electrical elements remotely in a first stage. The prototyping phase of the EIoT platform was developed using Mbed-enabled LoRa nodes coupled to electrical elements with the corresponding instrumentation, a LoRaWAN network, and a custom application server;then, all the components of an IoT network were considered. Some results of the implementation are presented, which demonstrate the suitability of the EIoT platform to address several applications of the electrical industry. The results also expose promising opportunities to deal with data processing and analytics, integrate more IoT protocols, and consolidate a complete IoT ecosystem in the electrical industry and the smart grids in further researches.
The fifth-generation (5G) network provides support for a wide variety of systems, including applications that demand the highest level of security as well as dependable communication. Because of recent advancements in...
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The fifth-generation (5G) network provides support for a wide variety of systems, including applications that demand the highest level of security as well as dependable communication. Because of recent advancements in smart devices, we are currently experiencing an explosion in the generation of data as well as a heterogeneity that necessitates the development of new network solutions for improved traffic analysis and comprehension. In order to automatically manage the massive amounts of data, these solutions need to be both intelligent and scalable. It is now feasible and easy to deploy machine learning (ML) to solve complex problems, and its effectiveness has been validated in a number of different domains. This is due to the progress that has been made in high-performance computing. It is anticipated that the deployment of 5G wireless communication systems will start in the year 2020. The traffic management for 5G networks will present significant technical challenges due to the introduction of new use cases, new technologies, and new network architectures. In this paper, we have concentrated on analyzing network data traffic for 5G Network using an ensemble method known as Bagging ensemble with Random Forest. Bootstrap sampling is utilized in the standard ensemble method known as “bagging.” The random forest technique is an improvement on the bagging method that can result in better variable selection. First, we will go over the concept of bagging, and then we will go over the enhancement that brought about random forest. The random forest algorithm is objective because it consists of multiple trees, each of which is trained on a different subset of the data. When you have both categorical and numerical features to work with, the random forest algorithm performs particularly well. On the basis of the test data, the classification accuracy is an average of 96 percent, significantly outperforming other methods.
Identification of License plates of vehicles is significant in various monitoring and security applications. This paper involves two major processes: image processing of the License plate and classification of the ind...
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In any security process the role of trust anchors and trust roots have a complex interaction and applying them to the transport domain where many different forms of trust relationship have to work together is going to...
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ISBN:
(纸本)9783030395124;9783030395117
In any security process the role of trust anchors and trust roots have a complex interaction and applying them to the transport domain where many different forms of trust relationship have to work together is going to be one of greatest of the problems to surmount. ITS and CAV are data centric information systems in which the provenance of the data in the system is key to the success of the system. Provenance and integrity are underpinnings of trust, but in CAV and ITS there is no a priori knowledge of the source and value of data. This means that the provenance of a signal or message from the infrastructure is unlikely to be tested in advance and the verification of trust needs to be applied on demand for each message. Determining trust distribution in the transport infrastructure is one of the biggest unanswered questions regarding the viability of CAV.
One of the important research topics and areas that is attracting significant interest and attention globally is 'big data'. While big data contribute towards the quality of decision-making, it also assists in...
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ISBN:
(纸本)9789811393648;9789811393631
One of the important research topics and areas that is attracting significant interest and attention globally is 'big data'. While big data contribute towards the quality of decision-making, it also assists in the development of and extending the knowledge in this area by harnessing available technology. This research presents and discusses the literature related to the quality of big data and its impact on the quality of decision-making. Adescriptive methodology approach was also adopted by reviewing the literature of published and unpublished scientific research along with a survey in the form of a questionnaire involving participants from Abu Dhabi Police Agencies to collect their views and opinions in this area. The results from the literature review and survey led to proposing a theoretical, conceptual model according to the quantitative and numerical methodology. The findings of this research have revealed that the quality of big data predicts the quality of decision-making and that the quality of big data in Abu Dhabi Governmental Organisations (ADGO) plays a significant role in the quality of decision-making.
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