Long Short-Term Memory and Gated Recurrent Unit-based networks are examined for short-term load forecasting for the Greek power system, where predictions of the next hour's load are made for the whole year. The re...
Long Short-Term Memory and Gated Recurrent Unit-based networks are examined for short-term load forecasting for the Greek power system, where predictions of the next hour's load are made for the whole year. The recurrent property of the forecasters has the advantage to allow the use of a reduced input set since no prior knowledge of the most suitable previous loads is required for the model to identify the temporal relations that exist in the load time-series. An extensive simulation analysis is conducted, to evaluate the forecasters' performance and to highlight their particular learning characteristics. Both deep learning-based forecasters perform very efficiently, with LSTM achieving an average percentage error of 1.18% and a root mean squared error of 83.8 MW, while GRU performs similarly with respective values of 1.17% and 83.4 MW.
Based on one of the fundamental principles of the educational model of the European Higher Education Area concerning the development of the capacity to achieve lifelong learning, this project has been developed in whi...
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This study sought to develop and test a machine learning based prototype of a smart home security system for Kampala Metropolitan area in Uganda. The researchers used a Design Science Research (DSR) method to execute ...
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ISBN:
(数字)9798350387902
ISBN:
(纸本)9798350387919
This study sought to develop and test a machine learning based prototype of a smart home security system for Kampala Metropolitan area in Uganda. The researchers used a Design Science Research (DSR) method to execute the project. The researchers identified a problem- which was high level of insecurity and crimes around homes in Kampala and its metropolitan areas, defined objectives, collected requirements, designed and developed the artifact, then demonstrated, evaluated, and communicated the artifact to stakeholders. The team created a working prototype of a home-security system that was later tested, demonstrated, validated among potential users. Practically, this project was implemented in a simulated environment using Tinkercad Arduino software. The developed system prototype was simulated on screen and tested on at least one home to ensure its effectiveness in reducing unauthorized entry, robbery, and other forms of crimes that are widely prevalent in Kampala today. One limitation of the project was that Arduino board used was quite limited on the number of pins that were available for use. The initial project idea had featured a temperature sensor to that was intended to regulate the temperature in the home by making use of the fan. However, the researchers did not implement this due to the limited pins and the capacity of the Arduino Uno R3 board that was used. Higher capacity industrial tools could provide a more realistic design of a similar system. The project simulated an environment of a smart home security system that can be used to detect and reduce crime. This study is part of a wider project to test ML and IoT systems in building secure smart homes. The authors envisage the application on more advanced ML algorithms and techniques in improving the system.
The maritime sector is an industry that faces significant and various challenges related to cyber security and data management, such as fraud and user authentication. Therefore, there is a need for a secure solution t...
The maritime sector is an industry that faces significant and various challenges related to cyber security and data management, such as fraud and user authentication. Therefore, there is a need for a secure solution that can effectively manage data transactions while resolving digital identity. A biometric signature application in blockchain for fighting fraud and fake identities may provide a solution in the maritime sector. This research proposes a biometric signature and an IPFS network-blockchain framework to address these challenges. This paper also discusses the proposed framework's cyber security challenges that threaten behavioral biometric security.
In 1935, Max Zorn introduced Zorn's lemma with the intention of shortening proofs in algebra that had previously used the Axiom of Choice or the Well-Ordering theorem. However, there are several applications in op...
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A multi-layer photonic spiking convolutional neural network is presented, based on miniaturized VCSELs, targeting image classification. Spatial information is encoded using a time multiplexing scheme providing a radic...
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In this paper, multiple relay selection (MRS) schemes for untrusted unmanned aerial vehicle (UAV)-enabled networks are proposed. In this context, various machine learning (ML) models are employed to improve secrecy pe...
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Observational learning is a promising approach to enable people without expertise in programming to transfer skills to robots in a user-friendly manner, since it mirrors how humans learn new behaviors by observing oth...
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In this paper, we evaluate the performance of a vehicular ad hoc network that enables Vehicle-to-Everything (V2X) communication considering direct and indirect packet transmission. As a performance indicator, we use t...
In this paper, we evaluate the performance of a vehicular ad hoc network that enables Vehicle-to-Everything (V2X) communication considering direct and indirect packet transmission. As a performance indicator, we use the blocking probability due to the unavailability of resources. For the blocking probability calculation, we utilize two loss models from the teletraffic theory. The results demonstrate that both the capacity of the V2X links and the number of hops in the multi-hop transmission significantly affect the blocking probability of a request for service and consequently the QoS.
Conformance monitoring is crucial for ensuring the safe operation of unmanned aerial vehicles (UAVs). It aims to alert relevant parties to any deviations from authorized flight plans. The European Union Aviation Safet...
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