A predictive simulation is built on a conceptual model (e.g., to identify relevant constructs and relationships) and serves to estimate the potential effects of 'what-if' scenarios. Developing the conceptual m...
ISBN:
(纸本)9798350369663
A predictive simulation is built on a conceptual model (e.g., to identify relevant constructs and relationships) and serves to estimate the potential effects of 'what-if' scenarios. Developing the conceptual model and plausible scenarios has long been a time-consuming activity, often involving the manual processes of identifying and engaging with experts, then performing desk research, and finally crafting a compelling narrative about the potential futures captured as scenarios. Automation could speed-up these activities, particularly through text mining. We performed the first review on automation for simulation scenario building. Starting with 420 articles published between 1995 and 2022, we reduced them to 11 relevant works. We examined them through four research questions concerning data collection, extraction of individual elements, connecting elements of insight and (degree of automation of) scenario generation. Our review identifies opportunities to guide this growing research area by emphasizing consistency and transparency in the choice of datasets or methods.
Smart healthcare uses technology such as wearable devices and the Internet of Things to dynamically retrieve/access information, which is important for people who require continuous monitoring, that cannot be provided...
详细信息
Application of Unmanned Aerial Vehicles (UAVs) as small airborne base stations is gradually becoming a research hotspot in the field of wireless communications. With the flexible deployment, wide coverage and low cost...
详细信息
ISBN:
(数字)9798331517786
ISBN:
(纸本)9798331517793
Application of Unmanned Aerial Vehicles (UAVs) as small airborne base stations is gradually becoming a research hotspot in the field of wireless communications. With the flexible deployment, wide coverage and low cost, UAV communications show great potential in the fields of emergency rescue, environmental monitoring and military operations. In particular, the easier availability of line-of-sight (LOS) links for UAVs makes its combination with millimetre wave (mmWave) technology significantly enhance the communication bandwidth and data transfer rate. However, the very limited coverage of mmWave communications greatly affects the actual data rates provided by small aerial base stations of mmWave UAVs, especially considering user movement on the ground. In this paper, we study the joint optimisation problem of UAV deployment, user association, spectrum resource allocation in millimetre-wave heterogeneous networks, and explore the impact of different user movement models on system performance. Given that this problem is NP-hard, our paper proposes an MCR-SAC method to maximize the network’s total throughput. Simulation results demonstrate an average 18% improvement in total transmission rate compared to the conventional.
We introduce an application-specific c ircuit t hat c an b e programmed t o efficiently perform blind carrier phase recovery for different modulation formats. A circuit implementation that supports QPSK/16/32/64QAM is...
The healthcare system has become more reliant on the data collection capabilities of fast evolving IoT devices. Patient healthcare records (PHR) now contain additional information as a result. However, securing identi...
详细信息
The fifth generation (5G) is now widely used to access network services due to the emergence of the Internet of Things (IoT) and mobile devices. To secure 5G communication, the Third Generation Partnership Project (3G...
详细信息
ISBN:
(数字)9798350381993
ISBN:
(纸本)9798350382006
The fifth generation (5G) is now widely used to access network services due to the emergence of the Internet of Things (IoT) and mobile devices. To secure 5G communication, the Third Generation Partnership Project (3GPP) organization created the 5G-Authentication and Key Agreement (AKA) protocol. Security evaluations have found a number of problems in the 5G-AKA, including a violation of perfect forward secrecy, a traceability attack, and denial of service (DoS) attacks. To address the shortcomings of 5G-AKA, several enhanced versions have been developed. However, it has been shown that either these versions are expensive or do not address security issues. Additionally, less effort is put into providing security when a user utilizes roaming mobile services while a malicious Serving Network (SN) is present. This paper introduces an authentication mechanism to handle the above issues. In addition to this, a handover mechanism is also designed for re-connection. The authentication and handover phase security assessment uses the mathematical model Real-Or-Random (ROR), AVISPA, and Scyther tool. Furthermore, the performance comparison depicts that the authentication and handover phase is more efficient than existing protocols. An assessment of the smart contract function’s cost and effectiveness is also provided.
Microservices is an architectural style that promotes structuring an application as a collection of loosely coupled fine-grained services. Due to its support for continuous integration and agile development, it has be...
Microservices is an architectural style that promotes structuring an application as a collection of loosely coupled fine-grained services. Due to its support for continuous integration and agile development, it has become increasingly popular in different application domains. Since each microservice typically accesses different data, while composing complex applications, it is hard to monitor which data are getting accessed in the entire application workflow. This raises a serious concern over privacy protection, especially in the domains that require handling sensitive data. To guarantee privacy preservation, we need to identify the constraints that should be monitored by data analysis tools in runtime. In this paper, we demonstrate how formal modelling can be used as a basis for deriving monitoring constraints in the applications developed in the microservices architectural style. We formalise modelling patterns for specifying applications composed of microservices, data privacy constraints and demonstrate how to identify privacy violations in runtime.
Our research presents a novel method for automatically correcting the pitch of human vocals using a data-driven approach. Unlike existing commercial systems, which often shift vocal notes to predefined pitches or the ...
Our research presents a novel method for automatically correcting the pitch of human vocals using a data-driven approach. Unlike existing commercial systems, which often shift vocal notes to predefined pitches or the closest pitch in a twelve-tone scale, here pitch is treated as a continuous value. This allows for greater flexibility in singing performances, including improvisation and harmonization. The system is developed and a neural network is trained by using a dataset of 4,702 karaoke from Sumel Inc. which had a great intonation. This model is trained in such a way that it learns to make corrections using the incorrect intonations also for the different pitch variations. The flaws in the previous work was monotonous pitch consideration within a controlled environment. To overcome this our system was proposed, the network architecture also integrates the convolutional layers which is then processed by gated recurrent units, which have shown promising performance in real-world score-free singing pitch correction, also known as auto tuning. The anticipated convolutional neural network accurateness is 93 % and error rate 7%.
In recent years, with the rapid development of the mobile Internet, it has become easier for users to read news and corresponding comments. Most people get used to reading news on-line. However, sociologists have show...
详细信息
Speech emotion recognition is an area of research dedicated to identifying and categorizing emotions expressed through speech. Its purpose is to comprehend and interpret the emotional content conveyed in spoken words,...
Speech emotion recognition is an area of research dedicated to identifying and categorizing emotions expressed through speech. Its purpose is to comprehend and interpret the emotional content conveyed in spoken words, leveraging signal processing techniques, feature extraction algorithms, and machine learning models. The ultimate aim is to apply this knowledge in diverse applications such as human-computer relation, affective computing, and mental health diagnosis. Although the complexity and variability of emotional speech present significant challenges, recent years have witnessed notable progress through the development of advanced algorithms and the utilization of extensive training datasets. Here we proposed a CNN network pattern for speech emotion recognition for the bench mark datasets and got the accuracy of 88% for the convolutional neural network model.
暂无评论