The development of the Internet of Things (IoT) and communication technologies has led to the emergence of the multimedia IoT. The multimedia IoT contributes to a variety of multimedia applications, that can capture a...
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ISBN:
(数字)9798331519957
ISBN:
(纸本)9798331519964
The development of the Internet of Things (IoT) and communication technologies has led to the emergence of the multimedia IoT. The multimedia IoT contributes to a variety of multimedia applications, that can capture and transmit large amounts of images or video sequences over an IoT network. Due to restricted resources, multimedia IoT devices must transmit less multimedia data while retaining accuracy. This can save energy and memory use and increase multimedia IoT network performance. This paper proposes an efficient lightweight image compression approach (ELiCA) for Multimedia Internet of Things. The proposed ELiCA starts dividing the captured image into equal-sized blocks and the Discrete Cosine Transform (DCT) is applied to each of them to produce the DCT coefficients. Then, the DCT coefficients are quantized. The output of the quantization process is reordered using zigzag process. Finally, the output files of the zigzag are compressed using the error-bounded lossy compression technique known as SZ developed specifically for High-Performance Computing (HPC) systems. The compressed file will be transmitted by the MIoT device. The proposed ELiCA is evaluated using real sensed images and based on real IoT devices to show the efficiency of the proposed approach. The ELiCA presents better results compared with JPEG in terms of compression ratio, PSNR, and SSIM.
ZusammenfassungEs wird gezeigt, dass sich KoitersL2-Fehlerschätzung für die Lösung linearer elastischer Randwertprobleme, die ein modifiziertes angenähertes Funktional der Verzerrungsenergie enthal...
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Zusammenfassung
Es wird gezeigt, dass sich KoitersL2-Fehlerschätzung für die Lösung linearer elastischer Randwertprobleme, die ein modifiziertes angenähertes Funktional der Verzerrungsenergie enthalten, auf die Lösung von Problemen erweitern lässt, in denen die Spannungs-Dehnungs-Beziehungen nur approximativ von einer Verzerrungsenergiedichte abgeleitet werden können. Die Resultate werden für Untersuchungen bei Schalen mit einer Mittelfläche konstanter Durch-schnittskrümmung und bestehend aus einem Material mit modifizierten Spannungs-Dehnungs-Beziehungen verwendet, um die geltenden Gleichungen zu vereinfachen.
It is rigorously proved that relative errors of order ε in the stress-strain relations of linear shell theory result in relative pointwise errors in the solution displacement field of order ε.
It is rigorously proved that relative errors of order ε in the stress-strain relations of linear shell theory result in relative pointwise errors in the solution displacement field of order ε.
This paper proposes and analyzes the performance of a prioritized error control scheme for time sensitive application on the wireless sensor network. As a modified version of IEEE 802.11 WLAN, the proposed scheme furt...
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For the Internet of Things security, it should be considered security risk environments such as various platforms and services including smart devices that can be mounted on household electric appliances, healthcare, ...
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Global mobility is undergoing a dramatic change as cars fuelled by fossil fuels give way to those with zero or extremely low tailpipe emissions. Every one of the parts in big battery packs normally don't have simi...
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ISBN:
(数字)9798331518578
ISBN:
(纸本)9798331518585
Global mobility is undergoing a dramatic change as cars fuelled by fossil fuels give way to those with zero or extremely low tailpipe emissions. Every one of the parts in big battery packs normally don't have similar properties and may corrupt essentially in view of assembling fluctuation and different elements. The performance and economics of the entire battery pack are impacted by the increased power waste from degraded battery modules. Additionally, the influence changes depending on the trip pattern. A variety of important factors, such as the age of the car, the internal resistance of the lithium-ion battery pack, awareness of grid energy pricing, and the distance driven, affect how much an electric vehicle (EV) costs to drive every day. It has used the grid's energy price data to optimise the cost of the typical driving cycle. Accurately forecasting battery behaviour reliability for the daily driving cycle is the aim of this project. The driver will be able to determine the best charging schedules, driving energy consumption, and excess battery energy with the aid of the reliability battery behaviour forecast. The driver can reduce the cost of travel both daily and over the battery's lifespan by having a previous understanding of the battery's behaviour, the grid's energy pricing, and the trip's duration.
The electrodynamics of wave reflection from conducting media lead to difficult mathematical problems because of the matching conditions which must be met at the interface between conductors and nonconductors. Simplifi...
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The electrodynamics of wave reflection from conducting media lead to difficult mathematical problems because of the matching conditions which must be met at the interface between conductors and nonconductors. Simplified boundary conditions have been proposed by Leontovitch and others which considerably simplify certain of the mathematical problems. We discuss the Leontovitch condition together with certain of its shortcomings and present a new method which overcomes some of the difficulties of the Leontovitch condition. The new method is a perturbation away from infinite conductivity which allows the solution of electrodynamics problems to be calculated to any order of accuracy in the quantity (ωε/σ)1/2 for some important cases. An instance in which the perturbation method fails is also discussed.
Many data structures give away much more information than they were intended to. Whenever privacy is important, we need to be concerned that it might be possible to infer information from the memory representation of ...
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Many data structures give away much more information than they were intended to. Whenever privacy is important, we need to be concerned that it might be possible to infer information from the memory representation of a data structure that is not available through its "legitimate" interface. Word processors that quietly maintain old versions of a document are merely the most egregious example of a general problem. We deal with data structures whose current memory representation does not reveal their history. We focus on dictionaries, where this means revealing nothing about the order of insertions or deletions. Our first algorithm is a hash table based on open addressing, allowing O(1) insertion and search. We also present a history independent dynamic perfect hash table that uses space linear in the number of elements inserted and has expected amortized insertion and deletion time O(1). To solve the dynamic perfect hashing problem we devise a general scheme for history independent memory alloca tion. For fixed-size records this is quite efficient, with insertion and deletion both linear in the size of the record. Our variable-size record scheme is efficient enough for dynamic perfect hashing but not for general use. The main open problem we leave is whether it is possible to implement a variable-size record scheme with low overhead.
*** is an innovative web-based game that takes creativity, guessing, and artificial intelligence and puts them together in a great combination. It is both an entertaining and educational game, enabling players to enha...
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*** is an innovative web-based game that takes creativity, guessing, and artificial intelligence and puts them together in a great combination. It is both an entertaining and educational game, enabling players to enhance their creativity and guessing skills while exploring AI capabilities interactively. The participants draw random words as they compete with an artificial intelligence model, which predicts drawings in real time. The AI component not only adds challenge and thrill but also demonstrates the capability of machine learning in interactive gaming. To create a highly precise doodle recognizer, a Long-term Recurrent Convolutional Network (LRCN) was employed, and it proved to be much better than the typical Convolutional Neural Networks (CNNs). The LRCN model achieved 90% accuracy in the top-1 score and 97% in the top-3 score, which is a measure of its high level of prediction. Relative to CNNs, which were overfitting (training loss: 36%, validation loss: 53%), LRCN demonstrated a substantial learning curve, stabilizing at a final loss of 39%, thereby offering better resilience. Furthermore, LRCN outperformed CNN, and therefore particularly has been found useful in dynamic gaming conditions. *** is more than just for fun, providing interesting commentary on the domain of AI-based sketch recognition and the viability of deep learning algorithms in real time. The wide variety of categories and questions in the game makes it an enjoyable experience, as users are challenged to sharpen their creativity and intellectual skills while engaging with advanced AI technologies.
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