Optimizer based on Spiking Neural-oscillator Networks (OSNNs) are one of the deterministic PSO methods, which are based on dynamics of spiking neural-oscillator networks. In OSNNs, each particle consists of plural spi...
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ISBN:
(数字)9798350330991
ISBN:
(纸本)9798350331004
Optimizer based on Spiking Neural-oscillator Networks (OSNNs) are one of the deterministic PSO methods, which are based on dynamics of spiking neural-oscillator networks. In OSNNs, each particle consists of plural spiking oscillators which are coupled with other spiking oscillators by the Ring 1-way network. The Ring 1-way network affects search performances of OSNNs. However, an effectiveness of the Ring 1-way network has not been clarified. In this study, we theoretically analyze the Ring 1-way OSNNs in more detail. In addition, in order to demonstrate analytical results, we conduct numerical simulations and discuss the simulation results.
Addressing the growing challenge of combating international crime involves the development of secure and efficient methodologies that allow Law Enforcement Agencies to exchange information seamlessly, without being hi...
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ISBN:
(数字)9798350372878
ISBN:
(纸本)9798350372885
Addressing the growing challenge of combating international crime involves the development of secure and efficient methodologies that allow Law Enforcement Agencies to exchange information seamlessly, without being hindered by time-consuming bureaucratic processes. In this context, we present a solution centered on facial biometric search methodologies. Our approach underscores the importance of employing accurate and reliable methods to assess image data similarity, particularly in the domain of facial images, which pose unique challenges due to subtle variations. We propose a comprehensive solution that harnesses hashing techniques and homomorphic encryption. By doing so, our approach ensures secure data exchange while safeguarding confidentiality and integrity. We firmly believe that our approach will substantially improve collaboration in law enforcement efforts and make significant contributions to global security.
Digital transformation and predictive maintenance are still some of the key challenges faced by the industrial sector as it moves towards Industry 4.0. However, the lack of resources, experienced personnel, and the ab...
Digital transformation and predictive maintenance are still some of the key challenges faced by the industrial sector as it moves towards Industry 4.0. However, the lack of resources, experienced personnel, and the absence of digital-savvy culture in manufacturing companies, often hinder the adoption of the required technologies. In this context, maintenance is a required process to ensure the smooth and continuous operation of the production, but to this day, engineers are still required to physically inspect equipment on site. By applying digital technologies, a predictive maintenance framework will enable the industry to maximize the life of the equipment and to act on time in order to prevent failures and thus reduce costs and optimize maintenance efficiency. In this effort, integrating such technologies and the required modern computing devices for monitoring legacy industrial equipment remains a challenge. Therefore, in this paper, we present a low-cost IIoT system for an AI-based predictive maintenance of machinery in a real-world industrial environment. In specific, a data collection system, consisting of a Raspberry Pi device and several sensors (namely, an accelerometer, temperature sensors and a microphone), was designed and developed. The collected data was then utilized to feed a deep-learning LSTM-autoencoder model for anomaly detection through a semi-supervised learning approach. Despite the small amount of data collected, the model is able to effectively detect anomalies. Finally, ways in which the existing system can be improved are proposed.
Segmentation of cardiac magnetic resonance images (MRI) is crucial for the analysis and assessment of cardiac function, helping to diagnose and treat various cardiovascular diseases. Most recent techniques rely on dee...
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The continued improvement and development of study programmes content for mutual recognition of study programmes among the largest technical universities in the Baltic region provides a very good opportunity for regio...
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Broadcasting stands as a vital function within wireless sensor networks (WSNs), where nodes disseminate messages throughout the entire network, radiating in all possible directions. Our focus lies on the issue of thre...
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ISBN:
(数字)9798331536756
ISBN:
(纸本)9798331536763
Broadcasting stands as a vital function within wireless sensor networks (WSNs), where nodes disseminate messages throughout the entire network, radiating in all possible directions. Our focus lies on the issue of three-dimensional broadcasting, involving n sensors/robots positioned uniformly across a three-dimensional space. We propose an exponentially fast hybrid collaborative broadcasting algorithm in three-dimensional space "growing ball" through successive propagation steps. We study the effect of various parameters such as the density of the growing ball (ρ), distance (d), the energy emitted by node (E emit ), and ϵ used by the collaborative broadcast. Our approach is based on the idea of dividing the 3D space into two halves that reduce mathematical intricacy. The number of nodes N k in the k th step of the growing ball is the factor of (1+ϵ) k implies the exponential fast broadcast.
An autonomous mobile robot system is a distributed system consisting of mobile computational entities (called robots) that autonomously and repeatedly perform three operations: Look, Compute, and Move. Various problem...
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Residue Number Systems (RNS) offer a promising approach to enhancing the computational efficiency of Fully Homomorphic Encryption (FHE). This paper proposes an efficient base conversion method for RNS, leveraging para...
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ISBN:
(数字)9798350356830
ISBN:
(纸本)9798350356847
Residue Number Systems (RNS) offer a promising approach to enhancing the computational efficiency of Fully Homomorphic Encryption (FHE). This paper proposes an efficient base conversion method for RNS, leveraging parallel Processing Unit (PU) cores, where each PU core operates under different moduli, along with a Karatsuba-based Barrett modular multiplier to accelerate modular arithmetic in homomorphic encryption schemes. Our approach addresses the computational bottleneck of base conversions in FHE by utilizing optimized parallelism and efficient multiplication methods. Experimental results show that, with nearly the same latency for the computing unit, the proposed design can achieve higher throughput for implementing base conversion (BConv). The performance is further evaluated with different parallel core configurations (2, 3, and 6 cores), and these scenarios are compared against a single-core implementation. The design with 6 parallel cores achieves more than 5Gbps, demonstrating the significant benefit of increased parallelism for BConv in FHE operations.
Digital Marketing is a product marketing strategy using digital media and internet networks. Nowadays, digital marketing is a necessity for companies that thrive in the digital world. It greatly affects the growth of ...
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The current P4 programmability model assumes that a P4 programmable device is owned and controlled by a single tenant. However, in typical NFV scenarios, support for multiple tenants is desirable. When each tenant may...
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ISBN:
(数字)9783903176669
ISBN:
(纸本)9798331505158
The current P4 programmability model assumes that a P4 programmable device is owned and controlled by a single tenant. However, in typical NFV scenarios, support for multiple tenants is desirable. When each tenant may want to deploy their own P4 pipeline offering different network functions (NF), supporting multiple co-existing tenant pipelines on a single platform is difficult because it requires pipeline merging, control plane support, and resource management of the platform. In this paper, we present P4-MTAGG, a novel framework for flexibly deploying multiple P4 programmable NFs on a programmable match-action pipeline while supporting multiple tenants. P4-MTAGG consists of i) novel compiler-add-ons for automatic merging multiple P4-pipelines, ii) p4runtime-proxy to allow for control plane access of the aggregated pipelines together with policy-based resource management for the P4 target, and iii) orchestrator to automate the provisioning of a network node utilizing aggregation either in a simulated or real hardware environment. In this demo, we show how P4-MTAGG aggregates multiple NFs of varying complexity in Mininet. The user can orchestrate the aggregation process through a GUI. The per-tenant traffic is routed through the set of NFs using segment routing. Through the GUI, the user can instruct the p4runtime-proxy to enforce per-tenant bandwidth limits, which configure the per-tenant available resources in the data plane.
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